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== Electron microscopy images ==
== Electron microscopy images ==
=== Useful resources ===
[https://www.google.com/maps/d/viewer?mid=1eQ1r8BiDYfaK7D1S9EeFJEgkLggMyoaT&usp=sharing Map of cryoEM microscopes and labs in the world]
[https://www.ebi.ac.uk/emdb/genealogy CryoEM genealogy]


=== Online courses and Learning material ===
=== Online courses and Learning material ===
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[https://www.jove.com/video/52311/do-s-don-ts-cryo-electron-microscopy-primer-on-sample-preparation Do's and don'ts on sample preparation]
[https://www.jove.com/video/52311/do-s-don-ts-cryo-electron-microscopy-primer-on-sample-preparation Do's and don'ts on sample preparation]


[http://nramm.nysbc.org/2017-workshop-lectures NRAMM Workshop 2017]
[http://nramm.nysbc.org/2017-workshop-lectures NRAMM Workshop 2017] [https://nccat.nysbc.org/activities/courses/nccat-spa-short-course-2022 (course slides)]


[https://www.youtube.com/user/SBGridTV/videos SBGrid videos about the programs they offer]
[https://www.youtube.com/user/SBGridTV/videos SBGrid videos about the programs they offer]
Line 104: Line 110:


[https://www.google.com/maps/d/u/0/viewer?mid=1eQ1r8BiDYfaK7D1S9EeFJEgkLggMyoaT&ll=-3.81666561775622e-14%2C-37.83892653579875&z=1 Map with CryoEM Facilities]
[https://www.google.com/maps/d/u/0/viewer?mid=1eQ1r8BiDYfaK7D1S9EeFJEgkLggMyoaT&ll=-3.81666561775622e-14%2C-37.83892653579875&z=1 Map with CryoEM Facilities]
[https://www.youtube.com/playlist?list=PLhiuGaXlZZeliWnyp_wtRqPr_QkX00um7 NCCAT Single Particle Analysis short course]
[https://algosb2023.loria.fr/lectures/ Algorithms for Structural Bioinformatics, AlgoSB2023, Cargese]
[https://cryoem.world/ One world CryoEM technical talks]
[https://www.youtube.com/@Cryo-EMAcademy Cryo-EMAcademy YouTube]
[https://www.diamond.ac.uk/Instruments/Biological-Cryo-Imaging/eBIC/Training/Courses-and-workshops/2025-EventsCW/eBIC-in-situ-Cryo-ET-Workshop-2025.html In Situ CryoET eBic]


=== Image formation ===
=== Image formation ===
Line 188: Line 204:
| [[2004Sorzano_Normalization]]
| [[2004Sorzano_Normalization]]
| Background noise is Gaussian
| Background noise is Gaussian
|-
| Paper
| [[2008Downing_Twin]]
| Theoretical analysis of the CTF correction algorithms
|-  
|-  


Line 453: Line 474:
| [[2021Egerton_Inelastic]]
| [[2021Egerton_Inelastic]]
| PSF of inelastic scattering
| PSF of inelastic scattering
|-
| Paper
| [[2021Himes_Simulation]]
| Simulation of TEM images with special attention to inelastic scattering
|-  
|-  


Line 458: Line 484:
| [[2021Glaeser_Fading]]
| [[2021Glaeser_Fading]]
| Defocus-dependent Thon-ring fading
| Defocus-dependent Thon-ring fading
|-
| Paper
| [[2021Singer_Wilson]]
| Detailed analysis of Wilson statistics
|-  
|-  


Line 466: Line 497:


| Paper
| Paper
| [[2022Ravikumar_SideChains]]
| [[2022Bharadwaj_Scattering]]
| Comparison of side-chain dispersion in protein structures determined by cryo-EM and X-ray crystallography
| Electron scattering properties and their use for map sharpening
|-  
|-  


|}
| Paper
 
| [[2022Heymann_PSSNR]]
=== Collection geometry ===
| Progressive Spectral Signal-to-Noise Ratio to assess quality and radiation damage
 
{|
 
| Chapter
| [[1980Hoppe_Wedge]]
| Missing wedge
|-  
|-  


| Paper
| Paper
| [[1987Radermacher_RCT]]
| [[2022Dickerson_Inelastic]]
| Random Conical Tilt and Single axis tilt
| The role of inelastic scattering in thick specimens
|-  
|-  


| Paper
| Paper
| [[1988Radermacher_RCT]]
| [[2022Kulik_TAAM]]
| Random Conical Tilt and Single axis tilt
| Theoretical 3D electron diffraction electrostatic potential maps of proteins
|-  
|-  


| Paper
| Paper
| [[1995Penczek_Dual]]
| [[2022Ravikumar_SideChains]]
| Dual axis tomography
| Comparison of side-chain dispersion in protein structures determined by cryo-EM and X-ray crystallography
|-  
|-  


| Paper
| Paper
| [[1997Mastronarde_Dual]]
| [[2023Bromberg_Complex]]
| Dual axis tomography
| CTF and Ewald sphere correction using complex-valued images
|-  
|-  


| Paper
| Paper
| [[2003Ludtke_FocusPairs]]
| [[2023Heymann_Ewald]]
| Focus pairs for single particles
| The Ewald sphere/focus gradient does not limit the resolution of cryoEM reconstructions
|-  
|-  


| Paper
| Paper
| [[2005Lanzavecchia_Conical]]
| [[2023McMullan_100kV]]
| Conical tomography
| CryoEM at 100kV
|-  
|-  


| Paper
| Paper
| [[2005Zampighi_Conical]]
| [[2023Schreiber_charge]]
| Conical tomography
| Time dynamics of charge buildup
|-  
|-  


| Paper
| Paper
| [[2006Leschziner_OT]]
| [[2023Shi_Compression]]
| Orthogonal Tilt
| Protein compression due to ice formation
|-  
|-  


| Paper
| Paper
| [[2006Messaoudi_Multiple]]
| [[2024Bochtler_Probes]]
| Multiple axis tomography
| X-rays, electrons, and neutrons as probes of atomic matter
|-  
|-  


| Paper
| Paper
| [[2012Kudryashev_FocusPairs]]
| [[2024Dickerson_magnification]]
| Focus pairs tomography
| Accurate determination of magnification using gold
|-  
|-  


| Paper
| Paper
| [[2014Hovden_TiltFocus]]
| [[2024Joosten_Roodmus]]
| Combining tilt series with focus series
| Simulation of micrographs of heterogeneous macromolecules
|-  
|-  


| Paper
| Paper
| [[2015Sorzano_RandomConicalTilt]]
| [[2024Parkhurst_IceSimulation]]
| General formulation of Random Conical Tilt
| Projections of amorphous ice simulation simulated with Gaussian Random Fields
|-
 
| Paper
| [[2017Hagen_DoseTomography]]
| Dose optimization for subtomogram averaging
|-
 
| Paper
| [[2017Tan_PreferredViews]]
| Solving preferred views problems through tilting
|-  
|-  


| Paper
| Paper
| [[2017Donati_Compressed]]
| [[2024Remis_Damage]]
| Compressed sensing for STEM
| Radiation damage revealed by phase plates
|-  
|-  


| Paper
| Paper
| [[2018Oveisi_Stereo]]
| [[2025Dickerson_Damage]]
| Stereo-vision with EM
| Reduced radiation damage at liquid helium temperature
|-  
|-  


| Paper
| Paper
| [[2018Cheng_BeamShift]]
| [[2025Wu_ZeroLossCCCorrected]]
| Fast image acquisition through beam-shift
| Imaging with chromatic aberration correction and zero loss electrons
|-  
|-  


| Paper
| Paper
| [[2019Wu_BeamShiftAndTilt]]
| [[2026Heymann_Ewald]]
| Fast image acquisition through beam-shift and beam tilt control
| The relationship between the Ewald sphere and exit wave explored using focal series electron micrographs
|-  
|-  


|}
|}


=== Sample preparation ===
=== Collection geometry ===


{|
{|


| Paper
| Chapter
| [[1982Dubochet_Sample]]
| [[1980Hoppe_Wedge]]
| Vitreous ice
| Missing wedge
|-  
|-  


| Paper
| Paper
| [[1986Lepault_Sample]]
| [[1987Radermacher_RCT]]
| Fast freezing
| Random Conical Tilt and Single axis tilt
|-  
|-  


| Paper
| Paper
| [[1995Dubochet_Sample]]
| [[1988Radermacher_RCT]]
| High-pressure freezing
| Random Conical Tilt and Single axis tilt
|-  
|-  


| Paper
| Paper
| [[1995VanMarle_Sample]]
| [[1995Penczek_Dual]]
| Sample damages in resin
| Dual axis tomography
|-  
|-  


| Paper
| Paper
| [[1998Adrian_Sample]]
| [[1997Mastronarde_Dual]]
| Cryo negative staining
| Dual axis tomography
|-  
|-  


| Paper
| Paper
| [[2002DeCarlo_Damage]]
| [[2003Ludtke_FocusPairs]]
| Radiation damage in cryonegative staining
| Focus pairs for single particles
|-  
|-  


| Paper
| Paper
| [[2002Hsieh_Sample]]
| [[2005Lanzavecchia_Conical]]
| Cryofixation
| Conical tomography
|-  
|-  


| Paper
| Paper
| [[2004AlAmoudi_Sample]]
| [[2005Zampighi_Conical]]
| CEMOVIS
| Conical tomography
|-  
|-  


| Paper
| Paper
| [[2008Studer_Sample]]
| [[2006Leschziner_OT]]
| Review on high pressure freezing
| Orthogonal Tilt
|-  
|-  


| Paper
| Paper
| [[2009Pierson_Sample]]
| [[2006Messaoudi_Multiple]]
| Review on sample preparation for electron tomography
| Multiple axis tomography
|-  
|-  


| Paper
| Paper
| [[2010Zhang_OpNS]]
| [[2012Kudryashev_FocusPairs]]
| Optimized negative staining (OpNS) for small protein and lipoprotein imaging
| Focus pairs tomography
|-  
|-  


| Paper
| Paper
| [[2012Zhang_Cryo-PS]]
| [[2014Hovden_TiltFocus]]
| Cryo-positive staining (Cryo-PS)
| Combining tilt series with focus series
|-  
|-  


| Paper
| Paper
| [[2014Russo_GoldGrids]]
| [[2015Sorzano_RandomConicalTilt]]
| Gold grids for single particles
| General formulation of Random Conical Tilt
|-  
|-  


| Paper
| Paper
| [[2015Cabra_Sample]]
| [[2017Hagen_DoseTomography]]
| Review on sample preparation for single particles with videos
| Dose optimization for subtomogram averaging
|-  
|-  


| Paper
| Paper
| [[2015Chari_ProteoPlex]]
| [[2017Tan_PreferredViews]]
| Fast evaluation of the structural stability
| Solving preferred views problems through tilting
|-  
|-  


| Paper
| Paper
| [[2016Passmore_Review]]
| [[2017Donati_Compressed]]
| Tutorial chapter on sample preparation
| Compressed sensing for STEM
|-  
|-  


| Paper
| Paper
| [[2016Razinkov_Vitrification]]
| [[2018Oveisi_Stereo]]
| New vitrification method
| Stereo-vision with EM
|-  
|-  


| Paper
| Paper
| [[2016Takizawa_Sample]]
| [[2018Cheng_BeamShift]]
| Review on sample preparation for EM
| Fast image acquisition through beam-shift
|-  
|-  


| Paper
| Paper
| [[2016Thompson_Sample]]
| [[2019Wu_BeamShiftAndTilt]]
| Review on sample preparation for EM
| Fast image acquisition through beam-shift and beam tilt control
|-  
|-  


| Paper
| Paper
| [[2017Arnold_BlottingFree]]
| [[2023Seifer_RevisedSaxton]]
| Blotting-free preparation
| Revised Saxton geometry for tilt series acquisition
|-
|-  
 
|}
 
=== Sample preparation ===


| Paper
{|
| [[2017Earl_review]]
| Review of sample preparation
|-


| Paper
| Paper
| [[2017Feng_SprayingPlunging]]
| [[1982Dubochet_Sample]]
| Spraying plunging
| Vitreous ice
|-
|-  


| Paper
| Paper
| [[2017He_FIB]]
| [[1986Lepault_Sample]]
| Cryo FIB lamella for TEM
| Fast freezing
|-
|-  


| Paper
| Paper
| [[2017Peitsch_Sample]]
| [[1995Dubochet_Sample]]
| iMEM: Isolation of Plasma Membrane for Cryoelectron Microscopy
| High-pressure freezing
|-
|-  


| Paper
| Paper
| [[2017Scapin_Storage]]
| [[1995VanMarle_Sample]]
| Cryo storage of samples
| Sample damages in resin
|-
|-  


| Paper
| Paper
| [[2017Schaffer_FocusedIonBeam]]
| [[1998Adrian_Sample]]
| Focused Ion Beam sample preparation for membrane proteins
| Cryo negative staining
|-
|-  


| Paper
| Paper
| [[2017Scherr_HydrogelNanomembranes]]
| [[2002DeCarlo_Damage]]
| Sample preparation for membrane proteins
| Radiation damage in cryonegative staining
|-
|-  


| Paper
| Paper
| [[2018Anderson_CLEM]]
| [[2002Hsieh_Sample]]
| Correlated light and EM
| Cryofixation
|-
|-  


| Paper
| Paper
| [[2018Arnold_Review]]
| [[2004AlAmoudi_Sample]]
| Review on sample preparation with special emphasis on microfluidic approaches
| CEMOVIS
|-
|-  


| Paper
| Paper
| [[2018Ashtiani_femtolitre]]
| [[2008Studer_Sample]]
| Delivery of femtolitre droplets using surface acoustic wave based atomisation for cryo-EM grid preparation
| Review on high pressure freezing
|-
|-  


| Paper
| Paper
| [[2018Dandey_Spotiton]]
| [[2009Pierson_Sample]]
| Spotiton, a device for vitrification
| Review on sample preparation for electron tomography
|-
|-  


| Paper
| Paper
| [[2018Gewering_Detergents]]
| [[2010Zhang_OpNS]]
| Detergent background in negative stain
| Optimized negative staining (OpNS) for small protein and lipoprotein imaging
|-
|-  


| Paper
| Paper
| [[2018Li_CLEM]]
| [[2012Zhang_Cryo-PS]]
| Correlated light and EM
| Cryo-positive staining (Cryo-PS)
|-
|-  


| Paper
| Paper
| [[2018Noble_Reducing]]
| [[2014Russo_GoldGrids]]
| Reducing particle adsorption
| Gold grids for single particles
|-
|-  


| Paper
| Paper
| [[2018Palovcak_Graphene]]
| [[2015Cabra_Sample]]
| Preparation of graphene-oxide cryo-EM grids
| Review on sample preparation for single particles with videos
|-
|-  


| Paper
| Paper
| [[2018Rice_Ice]]
| [[2015Chari_ProteoPlex]]
| Routine determination of ice thickness
| Fast evaluation of the structural stability
|-
|-  


| Paper
| Paper
| [[2018Schmidli_Miniaturized]]
| [[2016Passmore_Review]]
| Protein isolation and sample preparation
| Tutorial chapter on sample preparation
|-
|-  


| Paper
| Paper
| [[2018Wei_Grids]]
| [[2016Razinkov_Vitrification]]
| "Self-wicking" nanowire grids
| New vitrification method
|-
|-  


| Paper
| Paper
| [[2019DImprima_Denaturation]]
| [[2016Takizawa_Sample]]
| Protein denaturation at the air-water interface and how to prevent it
| Review on sample preparation for EM
|-
|-  


| Paper
| Paper
| [[2019Rubinstein_ultrasonic]]
| [[2016Thompson_Sample]]
| Ultrasonic specimen preparation device
| Review on sample preparation for EM
|-
|-  


| Paper
| Paper
| [[2019Song_FalconIII]]
| [[2017Arnold_BlottingFree]]
| Comparison of the modes of Falcon III
| Blotting-free preparation
|-
|-


| Paper
| Paper
| [[2020Cianfrocco_Wrong]]
| [[2017Earl_review]]
| What could go wrong?
| Review of sample preparation
|-
|-


| Paper
| Paper
| [[2020Egelman_Ice]]
| [[2017Feng_SprayingPlunging]]
| Problems with the ice
| Spraying plunging
|-
|-


| Paper
| Paper
| [[2020Fassler_Printing]]
| [[2017He_FIB]]
| 3D printed cell culture grid holder
| Cryo FIB lamella for TEM
|-
|-


| Paper
| Paper
| [[2020Klebl_Deposition]]
| [[2017Peitsch_Sample]]
| Sample deposition onto CryoEM grids: sprays and jets
| iMEM: Isolation of Plasma Membrane for Cryoelectron Microscopy
|-
|-


| Paper
| Paper
| [[2020Maeots_TimeResolved]]
| [[2017Scapin_Storage]]
| Time resolved CryoEM by microfluidics
| Cryo storage of samples
|-
|-


| Paper
| Paper
| [[2020Tan_ThroughGrid]]
| [[2017Schaffer_FocusedIonBeam]]
| Through-grid wicking enables high-speed 1 cryoEM specimen preparation
| Focused Ion Beam sample preparation for membrane proteins
|-
|-


| Paper
| Paper
| [[2020Yoder_TimeResolved]]
| [[2017Scherr_HydrogelNanomembranes]]
| Time resolved CryoEM by light estimulation
| Sample preparation for membrane proteins
|-
|-


| Paper
| Paper
| [[2020Zachs_FIB]]
| [[2018Anderson_CLEM]]
| Automation for FIB milling
| Correlated light and EM
|-
|-


| Paper
| Paper
| [[2021Bieber_FIBET]]
| [[2018Arnold_Review]]
| Sample preparation for correlative FIB milling and CryoET
| Review on sample preparation with special emphasis on microfluidic approaches
|-
|-


| Paper
| Paper
| [[2021Budell_TimeResolved]]
| [[2018Ashtiani_femtolitre]]
| Time resolved CryoEM with Spotiton
| Delivery of femtolitre droplets using surface acoustic wave based atomisation for cryo-EM grid preparation
|-
|-


| Paper
| Paper
| [[2021Casasanta_Microchip]]
| [[2018Dandey_Spotiton]]
| Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy
| Spotiton, a device for vitrification
|-
|-


| Paper
| Paper
| [[2021Frechard_Preparation]]
| [[2018Gewering_Detergents]]
| Optimization of Sample Preparation
| Detergent background in negative stain
|-
|-


| Paper
| Paper
| [[2021Engstrom_Nitrogen]]
| [[2018Li_CLEM]]
| Samples vitrified in boiling nitrogen
| Correlated light and EM
|-
|-


| Paper
| Paper
| [[2021Jagota_GoldNanoparticles]]
| [[2018Noble_Reducing]]
| Gold nanoparticles to assess flexibility
| Reducing particle adsorption
|-
|-


| Paper
| Paper
| [[2021Jiang_MoAu]]
| [[2018Palovcak_Graphene]]
| Holey Gold Films on Molybdenum Grids
| Preparation of graphene-oxide cryo-EM grids
|-
|-


| Paper
| Paper
| [[2021Jonaid_Liquid]]
| [[2018Rice_Ice]]
| Liquid phase EM
| Routine determination of ice thickness
|-
|-


| Paper
| Paper
| [[2021Ki_Conformational]]
| [[2018Schmidli_Miniaturized]]
| Conformational Distribution of a Small Protein with Nanoparticle-Aided CryoEM
| Protein isolation and sample preparation
|-
|-


| Paper
| Paper
| [[2021Li_detergents]]
| [[2018Wei_Grids]]
| The effect of detergents on preferential orientations
| "Self-wicking" nanowire grids
|-
|-


| Paper
| Paper
| [[2021Voss_Melting]]
| [[2019DImprima_Denaturation]]
| Rapid melting and revitrification as an approach to microsecond time-resolved cryoEM
| Protein denaturation at the air-water interface and how to prevent it
|-
|-


| Paper
| Paper
| [[2021Zhang_Pegylation]]
| [[2019Rubinstein_ultrasonic]]
| Improving particle quality in cryo-EM by PEGylation
| Ultrasonic specimen preparation device
|-
|-


| Paper
| Paper
| [[2022Naydenova_Grid]]
| [[2019Song_FalconIII]]
| Integrated wafer-scale manufacturing of electron cryomicroscopy specimen supports
| Comparison of the modes of Falcon III
|-
|-


|}
| Paper
| [[2020Cianfrocco_Wrong]]
| What could go wrong?
|-


=== Automated data collection ===
| Paper
| [[2020Egelman_Ice]]
| Problems with the ice
|-


{|
| Paper
| [[2020Fassler_Printing]]
| 3D printed cell culture grid holder
|-


| Paper
| Paper
| [[1992Dierksen_Automatic]]
| [[2020Klebl_Deposition]]
| Automated data collection
| Sample deposition onto CryoEM grids: sprays and jets
|-  
|-


| Paper
| Paper
| [[1992Koster_Automatic]]
| [[2020Maeots_TimeResolved]]
| Automated data collection
| Time resolved CryoEM by microfluidics
|-  
|-


| Paper
| Paper
| [[1996Fung_Automatic]]
| [[2020Tan_ThroughGrid]]
| Automated data collection for tomography
| Through-grid wicking enables high-speed 1 cryoEM specimen preparation
|-  
|-


| Paper
| Paper
| [[2001Zhang_Automatic]]
| [[2020Yoder_TimeResolved]]
| Automated data collection: AutoEM
| Time resolved CryoEM by light estimulation
|-  
|-


| Paper
| Paper
| [[2003Ziese_Automatic]]
| [[2020Zachs_FIB]]
| Automated autofocusing
| Automation for FIB milling
|-  
|-


| Paper
| Paper
| [[2004Potter_Automatic]]
| [[2021Bieber_FIBET]]
| Automated sample loading
| Sample preparation for correlative FIB milling and CryoET
|-  
|-


| Paper
| Paper
| [[2004Zheng_Automatic]]
| [[2021Budell_TimeResolved]]
| Automated data collection
| Time resolved CryoEM with Spotiton
|-  
|-


| Paper
| Paper
| [[2005Lei_Automatic]]
| [[2021Casasanta_Microchip]]
| Automated data collection: AutoEM
| Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy
|-  
|-


| Paper
| Paper
| [[2005Suloway_Automatic]]
| [[2021Frechard_Preparation]]
| Automated data collection: Leginon
| Optimization of Sample Preparation
|-  
|-


| Paper
| Paper
| [[2007Yoshioka_RCT]]
| [[2021Engstrom_Nitrogen]]
| Automated Random Conical Tilt
| Samples vitrified in boiling nitrogen
|-  
|-


| Paper
| Paper
| [[2011Korinek_TOM2]]
| [[2021Jagota_GoldNanoparticles]]
| Automated acquisition with TOM2
| Gold nanoparticles to assess flexibility
|-  
|-


| Paper
| Paper
| [[2015Li_UCSFImage]]
| [[2021Jiang_MoAu]]
| Automated acquisition with UCSFImage
| Holey Gold Films on Molybdenum Grids
|-  
|-


| Paper
| Paper
| [[2016Gil_Fuzzy]]
| [[2021Jonaid_Liquid]]
| Real time decisions during acquisition with neuro-fuzzy method
| Liquid phase EM
|-  
|-


| Paper
| Paper
| [[2016Liu_TiltControl]]
| [[2021Ki_Conformational]]
| Accurate control of the tilt angle for electron tomography
| Conformational Distribution of a Small Protein with Nanoparticle-Aided CryoEM
|-  
|-


| Paper
| Paper
| [[2016Vargas_FoilHole]]
| [[2021Li_detergents]]
| Determination of image quality at low magnification
| The effect of detergents on preferential orientations
|-  
|-


| Paper
| Paper
| [[2017Alewijnse_Best]]
| [[2021Voss_Melting]]
| Best practices for managing large CryoEM facilities
| Rapid melting and revitrification as an approach to microsecond time-resolved cryoEM
|-  
|-


| Paper
| Paper
| [[2017Biyani_Focus]]
| [[2021Zhang_Pegylation]]
| Automatic processing of micrographs
| Improving particle quality in cryo-EM by PEGylation
|-  
|-


| Paper
| Paper
| [[2018Gomez_Facilities]]
| [[2022Chen_Detergents]]
| Use of Scipion at facilities
| Role of detergents in the air-water interface
|-  
|-


| Paper
| Paper
| [[2018Sorzano_Gain]]
| [[2022Levitz_Chameleon]]
| Estimation of the DDD camera gain or residual gain
| Effects of dispense-to-plunge speed on particle concentration, complex formation, and final resolution
|-  
|-


| Paper
| Paper
| [[2019Chreifi_TiltSeries]]
| [[2022Naydenova_Grid]]
| Rapid tilt-series acquisition for electron cryotomography
| Integrated wafer-scale manufacturing of electron cryomicroscopy specimen supports
|-  
|-


| Paper
| Paper
| [[2019Eng_ImageCompression]]
| [[2022Russo_Review]]
| 3D Reconstruction from compressed images
| Review of sample preparation issues
|-  
|-


| Paper
| Paper
| [[2019Eisenstein_FISE]]
| [[2022Scher_FIB]]
| Improved applicability and robustness of fast cryo-electron tomography data acquisition
| Sample preparation for FIB-SEM and Correlative microscopy
|-  
|-


| Paper
| Paper
| [[2019Hamaguchi_CryoARM]]
| [[2023Basanta_Graphene]]
| CryoARM data acquisition
| Fabrication of Monolayer Graphene-Coated Grids
|-  
|-
 
 
| Paper
| Paper
| [[2019Maluenda_Scipion]]
| [[2023Grassetti_Graphene]]
| Automated workflow processing for facilities
| Improving graphane monolayer sample preparation
|-  
|-


| Paper
| Paper
| [[2019Schorb_ET]]
| [[2023Han_Sample]]
| Automated acquisition in Electron Tomography
| Challenges in making ideal cryo-EM samples
|-  
|-


| Paper
| Paper
| [[2019Tegunov_Warp]]
| [[2023Liu_AirWater]]
| Automatic micrograph processing with Warp
| Review on sample preparation techniques to deal with the air-water interface
|-  
|-


| Paper
| Paper
| [[2019Thompson_Protocol]]
| [[2023Langeberg_RNAScaffold]]
| Protocol for EM acquisition
| RNA scaffolds for small proteins
|-  
|-


| Paper
| Paper
| [[2020Baxa_Facility]]
| [[2023Neselu_IceThickness]]
| Operational workflow in a facility
| Effect of ice thickness on resolution
|-  
|-


| Paper
| Paper
| [[2020Guo_EER]]
| [[2023Torino_TimeResolved]]
| Electron event representation for acquisition
| Device for the preparation of time-resolved CryoEM experiments
|-  
|-


| Paper
| Paper
| [[2020Li_Workflow]]
| [[2023Venien_Membrane]]
| Workflow for automatic reconstruction
| Review on the preparation of membrane proteins
|-  
|-


| Paper
| Paper
| [[2020Sader_Facility]]
| [[2023Zheng_Ultraflat]]
| Microscope installation and operation in a facility
| Uniform thin ice on ultraflat graphene grids
|-  
|-


| Paper
| Paper
| [[2020Schenk_CryoFlare]]
| [[2024Esfahani_SPOTRASTR]]
| CryoFlare, automatic data acquisition
| SPOT-RASTR: A sample preparation technique that overcomes preferred orientations
|-  
|-


| Paper
| Paper
| [[2020Stabrin_Transphire]]
| [[2024Abe_LEA]]
| TranSPHIRE: Automated and feedback-optimized on-the-fly processing for cryo-EM
| LEA proteins to reduce the air-water interface interaction
|-  
|-


| Paper
| Paper
| [[2020Weis_Acquisition]]
| [[2024Bhattacharjee_TimeResolved]]
| Suggestions for high-quality and high-throughput acquisition
| Time-resolved cryoEM with a microfluidic device
|-  
|-


| Paper
| Paper
| [[2021Feathers_Superresolution]]
| [[2024Harley_40]]
| Effects of superresolution and magnification on final resolution
| Pluge freezing over 40 degrees
|-  
|-


| Paper
| Paper
| [[2021Bouvette_Bisect]]
| [[2024Henderikx_Vitrojet]]
| Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography
| Use cases of Vitrojet
|-  
|-


| Paper
| Paper
| [[2021Chreifi_FISE]]
| [[2024Hsieh_MinIce]]
| Rapid tilt-series method for cryo-electron tomography: Characterizing stage behavior during FISE acquisition
| Minimization of the ice contamination for cryoET
|-  
|-


| Paper
| Paper
| [[2021Efremov_ComaCorrected]]
| [[2024Liu_Graphene]]
| Coma-corrected rapid single-particle cryo-EM data collection on the CRYO ARM 300
| Review of the use of graphene for grid preparation
|-  
|-


| Paper
| Paper
| [[2021Herzik_Setup]]
| [[2024Mueller_Facility]]
| Setup for parallel illumination
| Sample workflow at the facility
|-  
|-


| Paper
| Paper
| [[2021Kayama_Multipurpose]]
| [[2024Tuijtel_Lamellae]]
| Below 3 Å structure of apoferritin using a multipurpose TEM with a side entry cryoholder
| Optimizing lamellae for subtomogram averaging
|-  
|-


| Paper
| Paper
| [[2021Lane_NegativeBias]]
| [[2024Yadav_Orientation]]
| Negative potential bias for faster imaging
| Experimental factors affecting orientation distribution
|-  
|-


| Paper
| Paper
| [[2021Rheinberger_IceThickness]]
| [[2025Chen_Detergent]]
| Scripts to measure ice thickness
| Review on the use of detergents to extract membran proteins and their effects on CryoEM
|-  
|-


| Paper
| Paper
| [[2021Yang_CRIM]]
| [[2025Elad_Review]]
| Computer readable image markers (CRIM) for correlative microscopy
| Review of sample preparation for in situ protein visualization
|-  
|-


| Paper
| Paper
| [[2021Weis_Strategies]]
| [[2025Grant_Nanodisc]]
| Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition
| Review on the use of nanodiscs for sample preparation
|-  
|-


| Paper
| Paper
| [[2021Wypych_gP2S]]
| [[2025Gusach_Diffusion]]
| LIMS of microscope sessions
| Sample vitrification faster than protein diffusion
|-  
|-


| Paper
| Paper
| [[2021Yang_CLEM]]
| [[2025Haynes_OptimalIce]]
| Automated correlative microscopy
| Vitrification conditions for optimal ice thickness
|-  
|-


| Paper
| Paper
| [[2021Yonekura_Hole]]
| [[2025Sun_PlasmaMembranes]]
| Automated hole detection using YOLO
| Sample preparation pipeline for plasma membrane analysis by CryoET
|-  
|-
 
|}


| Paper
=== Automated data collection ===
| [[2022Peck_200]]
| High-speed high-resolution data collection on a 200 keV cryo-TEM
|-
 
|}
 
== Single particles ==
 
=== Automatic particle picking ===


{|
{|


| Paper
| Paper
| [[1982VanHeel_Detection]]
| [[1992Dierksen_Automatic]]
| Detection of particles in micrographs
| Automated data collection
|-  
|-  


| Paper
| Paper
| [[2001Nicholson_Review]]
| [[1992Koster_Automatic]]
| Review on automatic particle picking
| Automated data collection
|-  
|-  


| Paper
| Paper
| [[2001Zhu_Filaments]]
| [[1996Fung_Automatic]]
| Automatic identification of filaments in micrographs
| Automated data collection for tomography
|-  
|-  


| Paper
| Paper
| [[2004Sigworth_Detection]]
| [[2001Zhang_Automatic]]
| Classical detection theory and the cryo-EM particle selection problem
| Automated data collection: AutoEM
|-  
|-  


| Paper
| Paper
| [[2004Volkmann_ParticlePicking]]
| [[2003Ziese_Automatic]]
| An approach to automated particle picking from electron micrographs based on reduced representation templates
| Automated autofocusing
|-  
|-  


| Paper
| Paper
| [[2004Wong_ParticlePicking]]
| [[2004Potter_Automatic]]
| Model-based particle picking for cryo-electron microscopy
| Automated sample loading
|-  
|-  


| Paper
| Paper
| [[2004Zhu_Review]]
| [[2004Zheng_Automatic]]
| Review on automatic particle picking
| Automated data collection
|-  
|-  


| Paper
| Paper
| [[2007Chen_Signature]]
| [[2005Lei_Automatic]]
| Automatic particle picking program: Signature
| Automated data collection: AutoEM
|-  
|-  


| Paper
| Paper
| [[2007Woolford_SwarmPS]]
| [[2005Suloway_Automatic]]
| Automatic particle picking with several criteria, implemented in EMAN Boxer
| Automated data collection: Leginon
|-  
|-  


| Paper
| Paper
| [[2009Sorzano_MachineLearning]]
| [[2007Yoshioka_RCT]]
| Automatic particle picking based on machine learning of rotational invariants
| Automated Random Conical Tilt
|-  
|-  


| Paper
| Paper
| [[2011Arbelaez_Comparison]]
| [[2011Korinek_TOM2]]
| Evaluation of the performance of software for automated particle-boxing
| Automated acquisition with TOM2
|-
|-  


| Paper
| Paper
| [[2013Abrishami_MachineLearning]]
| [[2015Li_UCSFImage]]
| A pattern matching approach to the automatic selection of particles from low-contrast electron micrographs
| Automated acquisition with UCSFImage
|-
|-  


| Paper
| Paper
| [[2013Hauer_2013]]
| [[2016Gil_Fuzzy]]
| Automatic tilt pair detection in Random Conical Tilt
| Real time decisions during acquisition with neuro-fuzzy method
|-
|-  


| Paper
| Paper
| [[2013Hoang_ParallelGPUPicking]]
| [[2016Liu_TiltControl]]
| Parallel GPU-accelerated particle picking
| Accurate control of the tilt angle for electron tomography
|-
|-  


| Paper
| Paper
| [[2013Shatsky_ParticlePicking]]
| [[2016Vargas_FoilHole]]
| Automated particle correspondence and accurate tilt-axis detection in tilted-image pairs
| Determination of image quality at low magnification
|-
|-  


| Paper
| Paper
| [[2013Vargas_ParticleQuality]]
| [[2017Alewijnse_Best]]
| Automatic determination of particle quality
| Best practices for managing large CryoEM facilities
|-  
|-  


| Paper
| Paper
| [[2014Langlois_ParticlePicking]]
| [[2017Biyani_Focus]]
| Automatic particle picking
| Automatic processing of micrographs
|-  
|-  


| Paper
| Paper
| [[2015Scheres_SemiAutoPicking]]
| [[2018Gomez_Facilities]]
| Semi-automated selection of cryo-EM particles
| Use of Scipion at facilities
|-  
|-  


| Paper
| Paper
| [[2016Vilas_AutomaticTilt]]
| [[2018Sorzano_Gain]]
| Automatic identification of image pairs in untilted-tilted micrograph pairs
| Estimation of the DDD camera gain or residual gain
|-  
|-  


| Paper
| Paper
| [[2016Wang_DeepPicker]]
| [[2019Chreifi_TiltSeries]]
| A deep learning approach for fully automated particle picking
| Rapid tilt-series acquisition for electron cryotomography
|-  
|-  


| Paper
| Paper
| [[2017Rickgauer_Detection]]
| [[2019Eng_ImageCompression]]
| Picking by correlation
| 3D Reconstruction from compressed images
|-  
|-  


| Paper
| Paper
| [[2017Zhu_DeepEM]]
| [[2019Eisenstein_FISE]]
| Deep learning approach to picking
| Improved applicability and robustness of fast cryo-electron tomography data acquisition
|-  
|-  


| Paper
| Paper
| [[2018Huber_Helices]]
| [[2019Hamaguchi_CryoARM]]
| Automated tracing of helices
| CryoARM data acquisition
|-  
|-  


| Paper
| Paper
| [[2018Heimowitz_ApplePicker]]
| [[2019Maluenda_Scipion]]
| Automated particle picking
| Automated workflow processing for facilities
|-  
|-  


| Paper
| Paper
| [[2018Sanchez_DeepConsensus]]
| [[2019Schorb_ET]]
| Deep learning consensus of multiple automatic pickers
| Automated acquisition in Electron Tomography
|-  
|-  


| Paper
| Paper
| [[2019Alazzawi_Clustering]]
| [[2019Tegunov_Warp]]
| Use of clustering algorithms to find particles in micrographs
| Automatic micrograph processing with Warp
|-  
|-  


| Paper
| Paper
| [[2019Bepler_Topaz]]
| [[2019Thompson_Protocol]]
| Deep learning for particle picking
| Protocol for EM acquisition
|-  
|-  


| Paper
| Paper
| [[2019Carrasco_IP]]
| [[2020Baxa_Facility]]
| Use of standard image processing for particle picking
| Operational workflow in a facility
|-  
|-  


| Conference
| Paper
| [[2019Li_Deep]]
| [[2020Guo_EER]]
| Deep learning for particle picking without box size
| Electron event representation for acquisition
|-  
|-  


| Paper
| Paper
| [[2019Wagner_Cryolo]]
| [[2020Li_Workflow]]
| Deep learning for particle picking
| Workflow for automatic reconstruction
|-  
|-  


| Paper
| Paper
| [[2019Wang_Biobjective]]
| [[2020Maruthi_Automatic]]
| Biobjective function for robust signal detection
| Evaluation of MicAssess and CryoAssess
|-  
|-  


| Paper
| Paper
| [[2019Zhang_Pixer]]
| [[2020Sader_Facility]]
| Deep learning for particle picking
| Microscope installation and operation in a facility
|-  
|-  


| Paper
| Paper
| [[2020Sanchez_Cleaner]]
| [[2020Schenk_CryoFlare]]
| Deep learning for removing particles from the carbon edges, aggregations, contaminations, ...
| CryoFlare, automatic data acquisition
|-  
|-  


| Conference
| Paper
| [[2021Li_PickerOptimizers]]
| [[2020Stabrin_Transphire]]
| Removal of badly picked particles with Deep Learning
| TranSPHIRE: Automated and feedback-optimized on-the-fly processing for cryo-EM
|-  
|-  


| Paper
| Paper
| [[2021Ohashi_GRIPS]]
| [[2020Yokoyama_Good]]
| Two-pass picking with GRIPS
| Deep learning for determining good regions in a grid
|-  
|-  


| Conference
| [[2022Huang_DenoisingAndPicking]]
| Simultaneous denoising and picking with deep learning
|-


| Paper
| Paper
| [[2022Olek_Icebreaker]]
| [[2020Weis_Acquisition]]
| Ice thickness detection and its use for particle picking
| Suggestions for high-quality and high-throughput acquisition
|-  
|-  
|}
=== 2D Preprocessing ===
{|


| Paper
| Paper
| [[1978Carrascosa_matching]]
| [[2021Feathers_Superresolution]]
| Gray values matching by linear transformations
| Effects of superresolution and magnification on final resolution
|-  
|-  


| Paper
| Paper
| [[2003Rosenthal_DPR]]
| [[2021Bouvette_Bisect]]
| Contrast enhancement through DPR
| Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Normalization]]
| [[2021Chreifi_FISE]]
| Normalization procedures and their statistical properties.
| Rapid tilt-series method for cryo-electron tomography: Characterizing stage behavior during FISE acquisition
|-  
|-  


| Paper
| Paper
| [[2006Sorzano_Denoising]]
| [[2021Danev_Eval]]
| Strong denoising in wavelet space
| Evaluation of different automatic acquisition schemes
|-  
|-  


| Conference
| Paper
| [[2009Sorzano_Downsampling]]
| [[2021Efremov_ComaCorrected]]
| Differences between the different downsampling schemes
| Coma-corrected rapid single-particle cryo-EM data collection on the CRYO ARM 300
|-  
|-  


| Paper
| Paper
| [[2012Brilot_Movies]]
| [[2021Herzik_Setup]]
| Alignment of beam induced motion in direct detectors
| Setup for parallel illumination
|-  
|-  


| Paper
| Paper
| [[2012Campbell_Movies]]
| [[2021Kayama_Multipurpose]]
| Alignment of beam induced motion in direct detectors
| Below 3 Å structure of apoferritin using a multipurpose TEM with a side entry cryoholder
|-  
|-  


| Paper
| Paper
| [[2012Zhao_Denoising]]
| [[2021Lane_NegativeBias]]
| Denoising using an invariant Fourier-Bessel eigenspace
| Negative potential bias for faster imaging
|-  
|-  


| Paper
| Paper
| [[2013Norousi_Screening]]
| [[2021Rheinberger_IceThickness]]
| Screening particles to identify outliers
| Scripts to measure ice thickness
|-  
|-  


| Paper
| Paper
| [[2013Bai_ElectronCounting]]
| [[2021Yang_CRIM]]
| Electron counting and beam induced motion correction
| Computer readable image markers (CRIM) for correlative microscopy
|-  
|-  


| Paper
| Paper
| [[2013Li_ElectronCounting]]
| [[2021Weis_Strategies]]
| Electron counting and beam induced motion correction
| Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition
|-  
|-  


| Paper
| Paper
| [[2013Shigematsu_Movies]]
| [[2021Wypych_gP2S]]
| Drift correction for movies considering dark field
| LIMS of microscope sessions
|-  
|-  


| Paper
| Paper
| [[2013Vargas_ParticleQuality]]
| [[2021Yang_CLEM]]
| Automatic determination of particle quality
| Automated correlative microscopy
|-  
|-  


| Paper
| Paper
| [[2014Scheres_Movies]]
| [[2021Yonekura_Hole]]
| Beam induced motion correction
| Automated hole detection using YOLO
|-  
|-  


| Paper
| Paper
| [[2015Abrishami_Movies]]
| [[2022Bepler_Smart]]
| Alignment of direct detection device micrographs
| Smart data collection
|-  
|-  


| Paper
| Paper
| [[2015Grant_Anisotropic]]
| [[2022Bouvette_SmartScope]]
| Automatic estimation and correction of anisotropic magnification
| SmartScope
|-  
|-  


| Paper
| Paper
| [[2015Grant_OptimalExposure]]
| [[2022Flutty_bits]]
| Filter movies according to the radiation damage
| Bit-precision for SPA and ET
|-  
|-  


| Paper
| Paper
| [[2015Rubinstein_Alignment]]
| [[2022Hagen_Screening]]
| Frame alignment at the level of particle
| Screening of ice thickness using energy filter-based plasmon imaging
|-  
|-  


| Paper
| Paper
| [[2015Spear_DoseCompensation]]
| [[2022Hohle_Ice]]
| Effect of dose compensation on resolution
| Screening of ice thickness using interferometry
|-  
|-  


| Paper
| Paper
| [[2015Zhao_AnisotropicMagnification]]
| [[2022Peck_200]]
| Correction of anisotropic magnification
| High-speed high-resolution data collection on a 200 keV cryo-TEM
|-  
|-  


| Conference
| Paper
| [[2016Bajic_Denoising]]
| [[2022Peck_Montage]]
| Denoising and deconvolution of micrographs
| Montage electron tomography
|-  
|-  


| Paper
| Paper
| [[2016Jensen_RemovalVesicles]]
| [[2022Zhu_ElectronCounting]]
| Removal of vesicles in membrane proteins
| New algorithm for electron counting at the microscope
|-  
|-  


| Paper
| Paper
| [[2016Bhamre_Denoising]]
| [[2023Cheng_Leginon]]
| Denoising by 2D covariance estimation
| Smart data collection with Leginon
|-  
|-  


| Paper
| Paper
| [[2017Berndsen_EMPH]]
| [[2023Kim_Ptolemy]]
| Automated hole masking algorithm
| Smart data collection with Ptolemy
|-  
|-  


| Paper
| Paper
| [[2017McLeod_Zorro]]
| [[2023Last_Ice]]
| Movie alignment by Zorro
| Measuring the ice thickness with an optical device and a neural network
|-  
|-  


| Paper
| Paper
| [[2017Zheng_MotionCorr2]]
| [[2023Mendez_Pipelines]]
| Movie alignment by MotionCorr2
| Evaluation of pipelines for stream processing
|-  
|-  


| Paper
| Paper
| [[2018Ouyang_Denoising]]
| [[2024Bobe_Calibration]]
| Denoising based on geodesic distance
| CryoEM Calibration workflow
|-  
|-  


| Paper
| Paper
| [[2018Wu_ContrastEnhancement]]
| [[2024Eisenstein_SPACETomo]]
| Contrast enhancement
| Automated acquisition of tilt series
|-  
|-  


| Paper
| Conference
| [[2019Zivanov_BayesianBIM]]
| [[2024Fan_RL]]
| Bayesian correction of beam induced movement
| Reinforcement learning to optimize the microscope use
|-  
|-  


| Paper
| Paper
| [[2020Bepler_TopazDenoise]]
| [[2024Hatton_EMinsight]]
| Preprocessing of micrographs for better picking
| EMinsight: a tool to capture cryoEM microscope configuration and experimental outcomes for analysis and deposition
|-  
|-  


| Paper
| Paper
| [[2020Chung_2SDR]]
| [[2024Xu_Miffi]]
| PCA to denoise particles
| Miffi: automatic classification of micrographs
|-  
|-  


| Paper
| Paper
| [[2020Chung_Prepro]]
| [[2025Bhandari_Fast]]
| Preprocessing of particles for better alignment
| Data acquisition in EPU Fast mode
|-  
|-  


| Conference
|}
| [[2020Huang_SuperResolution]]
| Deep learning superresolution combination of frames
|-


| Paper
== Single particles ==
| [[2020Palovcak_noise2noise]]
| Noise2noise denoising of micrographs
|-


| Paper
=== Automatic particle picking ===
| [[2020Strelak_FlexAlign]]
| Continuous deformation model for aligning movie frames
|-
 
| Conference
| [[2021Fan_Denoising]]
| Particle denoising using vector diffusion maps
|-
 
|}
 
=== 2D Alignment ===


{|
{|


| Paper
| Paper
| [[1981Frank_Averaging]]
| [[1982VanHeel_Detection]]
| 2D averaging and phase residual
| Detection of particles in micrographs
|-  
|-  


| Paper
| Paper
| [[1982Saxton_Averaging]]
| [[2001Nicholson_Review]]
| 2D averaging using correlation
| Review on automatic particle picking
|-  
|-  


| Paper
| Paper
| [[1998Sigworth_ML2D]]
| [[2001Zhu_Filaments]]
| Maximum likelihood alignment in 2D
| Automatic identification of filaments in micrographs
|-  
|-  


| Paper
| Paper
| [[2003Cong_FRM2D]]
| [[2004Sigworth_Detection]]
| Fast Rotational Matching in 2D
| Classical detection theory and the cryo-EM particle selection problem
|-  
|-  


| Paper
| Paper
| [[2005Cong_FRM2D]]
| [[2004Volkmann_ParticlePicking]]
| Fast Rotational Matching in 2D introduced in a 3D Alignment algorithm
| An approach to automated particle picking from electron micrographs based on reduced representation templates
|-  
|-  


| Paper
| Paper
| [[2005Scheres_ML2D]]
| [[2004Wong_ParticlePicking]]
| Multireference alignment and classification in 2D
| Model-based particle picking for cryo-electron microscopy
|-  
|-  


| Paper
| Paper
| [[2016Aguerrebere_Limits]]
| [[2004Zhu_Review]]
| Fundamental limits of 2D translational alignment
| Review on automatic particle picking
|-  
|-  


| Paper
| Paper
| [[2010Sorzano_CL2D]]
| [[2007Chen_Signature]]
| Multireference alignment and classification in 2D
| Automatic particle picking program: Signature
|-  
|-  


| Conference
| [[2017Anoshina_Correlation]]
| New correlation measure for aligning images
|-


| Paper
| Paper
| [[2019Radermacher_Correlation]]
| [[2007Woolford_SwarmPS]]
| On the properties of cross correlation for the alignment of images
| Automatic particle picking with several criteria, implemented in EMAN Boxer
|-  
|-  


| Paper
| Paper
| [[2020Lederman_representation]]
| [[2009Sorzano_MachineLearning]]
| A representation theory perspective of alignment and classification
| Automatic particle picking based on machine learning of rotational invariants
|-  
|-  


| Paper
| Paper
| [[2020Marshall_Invariants]]
| [[2011Arbelaez_Comparison]]
| Recovery of an image from its invariants
| Evaluation of the performance of software for automated particle-boxing
|-  
|-


| Paper
| Paper
| [[2021Chen_Fast]]
| [[2013Abrishami_MachineLearning]]
| Fast alignment through Power Spectrum
| A pattern matching approach to the automatic selection of particles from low-contrast electron micrographs
|-  
|-


| Conference
| Paper
| [[2021Chung_CryoRALIB]]
| [[2013Hauer_2013]]
| Image alignment acceleration
| Automatic tilt pair detection in Random Conical Tilt
|-  
|-


| Paper
| Paper
| [[2021Heimowitz_Centering]]
| [[2013Hoang_ParallelGPUPicking]]
| Centering noisy images
| Parallel GPU-accelerated particle picking
|-  
|-


|}
| Paper
 
| [[2013Shatsky_ParticlePicking]]
=== 2D Classification and clustering ===
| Automated particle correspondence and accurate tilt-axis detection in tilted-image pairs
 
|
{|


| Paper
| Paper
| [[1981VanHeel_MSA]]
| [[2013Vargas_ParticleQuality]]
| Multivariate Statistical Analysis
| Automatic determination of particle quality
|-  
|-  


| Paper
| Paper
| [[1984VanHeel_MSA]]
| [[2014Langlois_ParticlePicking]]
| Multivariate Statistical Analysis
| Automatic particle picking
|-  
|-  


| Paper
| Paper
| [[2005Scheres_ML2D]]
| [[2015Scheres_SemiAutoPicking]]
| Multireference alignment and classification in 2D
| Semi-automated selection of cryo-EM particles
|-  
|-  


| Paper
| Paper
| [[2010Sorzano_CL2D]]
| [[2016Vilas_AutomaticTilt]]
| Multireference alignment and classification in 2D
| Automatic identification of image pairs in untilted-tilted micrograph pairs
|-  
|-  


| Paper
| Paper
| [[2011Singer_DiffusionMaps]]
| [[2016Wang_DeepPicker]]
| Classification in 2D based on graph analysis of the projections
| A deep learning approach for fully automated particle picking
|-  
|-  


| Paper
| Paper
| [[2012Yang_ISAC]]
| [[2017Rickgauer_Detection]]
| Iterative Stable Alignment and clustering
| Picking by correlation
|-  
|-  


| Paper
| Paper
| [[2014Sorzano_Outlier]]
| [[2017Zhu_DeepEM]]
| Outlier detection in 2D classifications.
| Deep learning approach to picking
|-  
|-  


| Paper
| Paper
| [[2014Zhao_Aspire]]
| [[2018Huber_Helices]]
| Fast classification based on rotational invariants and vector diffusion maps
| Automated tracing of helices
|-  
|-  


| Paper
| Paper
| [[2015Huang_Robust]]
| [[2018Heimowitz_ApplePicker]]
| Robust w-estimators of 2D classes
| Automated particle picking
|-  
|-  


| Paper
| Paper
| [[2016Kimanius_Accelerated]]
| [[2018Sanchez_DeepConsensus]]
| GPU Accelerated image classification and high-resolution refinement
| Deep learning consensus of multiple automatic pickers
|-  
|-  


| Paper
| Paper
| [[2016Reboul_Stochastic]]
| [[2019Alazzawi_Clustering]]
| Stochastic Hill Climbing for calculating 2D classes
| Use of clustering algorithms to find particles in micrographs
|-  
|-  


| Conference
| Paper
| [[2017Bhamre_Mahalanobis]]
| [[2019Bepler_Topaz]]
| 2D classification using Mahalanobis distance
| Deep learning for particle picking
|-  
|-  


| Paper
| Paper
| [[2017Wu_GTM]]
| [[2019Carrasco_IP]]
| 2D classification using Generative Topographic Mapping
| Use of standard image processing for particle picking
|-  
|-  


| Conference
| Conference
| [[2018Boumal_SinglePass]]
| [[2019Li_Deep]]
| Single pass classification
| Deep learning for particle picking without box size
|-  
|-  


| Conference
| Paper
| [[2018Shuo_Network]]
| [[2019Wagner_Cryolo]]
| 2D Clustering by network metrics
| Deep learning for particle picking
|-  
|-  


| Conference
| Paper
| [[2020Miolane_VAEGAN]]
| [[2019Wang_Biobjective]]
| 2D Analysis by deep learning
| Biobjective function for robust signal detection
|-  
|-  


| Conference
| Paper
| [[2021Rao_Wasserstein]]
| [[2019Zhang_Pixer]]
| Wasserstein K-Means for Clustering Tomographic Projections
| Deep learning for particle picking
|-  
|-  


|}
| Paper
| [[2020Sanchez_Cleaner]]
| Deep learning for removing particles from the carbon edges, aggregations, contaminations, ...
|-


=== 3D Alignment ===
| Conference
 
| [[2021Li_PickerOptimizers]]
{|
| Removal of badly picked particles with Deep Learning
|-


| Paper
| Paper
| [[1980Kam_AutoCorrelation]]
| [[2021Ohashi_GRIPS]]
| Reconstruction without angular assignment from autocorrelation function (reference free)
| Two-pass picking with GRIPS
|-  
|-  


| Paper
| Paper
| [[1986Goncharov_CommonLines]]
| [[2022Eldar_ASOCEM]]
| Angular assignment using common lines (reference free)
| Automatic segmentation of contaminations
|-
 
| Conference
| [[2022Huang_DenoisingAndPicking]]
| Simultaneous denoising and picking with deep learning
|-  
|-  


| Paper
| Paper
| [[1987VanHeel_CommonLines]]
| [[2022Kreymer_MTD]]
| Angular assignment using common lines (reference free)
| Expectation-Maximization approach to particle picking
|-  
|-  


| Paper
| Paper
| [[1988Provencher_Simultaneous]]
| [[2022Olek_Icebreaker]]
| Simultaneaous alignment and reconstruction
| Ice thickness detection and its use for particle picking
|-  
|-  


| Paper
| Paper
| [[1988Radermacher_RCT]]
| [[2022Zhang_EPicker]]
| Random Conical Tilt and Single axis tilt
| Particle picking based on continual learning
|-  
|-  


| Paper
| Paper
| [[1988Vogel_Simultaneous]]
| [[2023Dhakal_CryoPPP]]
| Simultaneaous alignment and reconstruction
| A public database for particle picking
|-  
|-  


| Paper
| Paper
| [[1990Gelfand_Moments]]
| [[2023Lucas_Baited]]
| Angular assignment using moments (reference free)
| Baited reconstruction with 2D template matching
|-  
|-  


| Paper
| Paper
| [[1990Goncharov_Moments]]
| [[2024Anuk_Auction]]
| Angular assignment using moments (reference free)
| Particle picking using combinatorial auction
|-  
|-  


| Paper
| Paper
| [[1990Harauz_Quaternions]]
| [[2024Cameron_REPIC]]
| Use of quaternions to represent rotations
| Consensus 2D particle picking using graphs
|-  
|-  


| Paper
| Paper
| [[1994Penczek_Real]]
| [[2024Fang_Swin]]
| Angular assignment using projection matching in real space
| SwinCryoEM: particle picking
|-  
|-  


| Paper
| Paper
| [[1994Radermacher_Radon]]
| [[2024Gyawali_CryoSegNet]]
| Angular assignment in Radon space
| CryoSegNet: particle picking
|-  
|-  


| Paper
| Paper
| [[1996Penczek_CommonLines]]
| [[2024Huang_Joint]]
| Angular assignment using common lines (reference free)
| Joint denoising and picking
|-  
|-  


| Paper
| Paper
| [[2003Rosenthal_DPR]]
| [[2025Chung_CRISP]]
| Angular assignment using DPR
| Particle picking with deep learning and Conditional Random Field layers
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Wavelet]]
| [[2025Dhakal_Benchmark]]
| Angular assignment in the wavelet space.
| Benchmark of particle picking with deep learning
|-  
|-  


| Paper
| Paper
| [[2005Jonic_Splines]]
| [[2025Neiterman_Frames]]
| Angular assignment in Fourier space using spline interpolation.
| Particle picking at the level of frames
|-  
|-  


| Paper
| Paper
| [[2005Yang_Simultaneous]]
| [[2025Ni_GTPick]]
| Simultaneaous alignment and reconstruction
| GTPick: Particle picking with deep learning
|-  
|-  


| Paper
| Paper
| [[2006Ogura_SimulatedAnnealing]]
| [[2025Zamanos_CryoEMMAE]]
| Angular asignment by simulated annealing
| Fully unsupervised particle picking using neural networks
|-  
|-  


| Paper
| Paper
| [[2007Grigorieff_Continuous]]
| [[2025Zhang_2DTMpValue]]
| Continuous angular assignment in Fourier space
| p-value of the 2D template matching SNR and z-scores
|-  
|-  


| Paper
|}
| [[2010Jaitly_Bayesian]]
 
| Angular assignment by a Bayesian method and annealing
=== 2D Preprocessing ===
|-
 
{|


| Paper
| Paper
| [[2010Sanz_Random]]
| [[1978Carrascosa_matching]]
| Random model method
| Gray values matching by linear transformations
|-
|-  


| Paper
| Paper
| [[2010Singer_Voting]]
| [[2003Rosenthal_DPR]]
| Detecting consistent common lines by voting (reference free)
| Contrast enhancement through DPR
|-
|-  


| Paper
| Paper
| [[2011Singer_SDP]]
| [[2004Sorzano_Normalization]]
| Angular assignment by semidefinite programming and eigenvectors (reference free)
| Normalization procedures and their statistical properties.
|-
|-  


| Paper
| Paper
| [[2012Giannakis_Scattering]]
| [[2006Sorzano_Denoising]]
| Construction of an initial volume, reference free, by graph analysis of the projections
| Strong denoising in wavelet space
|-
|-  


| Paper
| Conference
| [[2012Shkolnisky_Sync]]
| [[2009Sorzano_Downsampling]]
| Angular assignment by synchronization of rotations (reference free)
| Differences between the different downsampling schemes
|-
|-  


| Paper
| Paper
| [[2013Elmlund H_PRIME]]
| [[2012Brilot_Movies]]
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
| Alignment of beam induced motion in direct detectors
|-  
|-  


| Paper
| Paper
| [[2013Wang_LUD]]
| [[2012Campbell_Movies]]
| Angular assignment by least unsquared deviations (reference free)
| Alignment of beam induced motion in direct detectors
|-
|-  


| Paper
| Paper
| [[2014Vargas_RANSAC]]
| [[2012Zhao_Denoising]]
| Initial model using RANSAC (reference free)
| Denoising using an invariant Fourier-Bessel eigenspace
|-
|-  


| Paper
| Paper
| [[2015Joubert_Pseudoatoms]]
| [[2013Norousi_Screening]]
| Initial model based on pseudo-atoms
| Screening particles to identify outliers
|-  
|-  


| Paper
| Paper
| [[2015Singer_Kam]]
| [[2013Bai_ElectronCounting]]
| Reconstruction without angular assignment from autocorrelation function (reference free)
| Electron counting and beam induced motion correction
|-  
|-  


| Paper
| Paper
| [[2015Sorzano_Significant]]
| [[2013Li_ElectronCounting]]
| Statistical approach to the initial volume estimation (reconstruct significant)
| Electron counting and beam induced motion correction
|-  
|-  


| Paper
| Paper
| [[2016Cossio_BayesianGPU]]
| [[2013Shigematsu_Movies]]
| GPU implementation of the Bayesian 3D reconstruction approach
| Drift correction for movies considering dark field
|-  
|-  


| Conference
| Paper
| [[2016Michels_Heterogeneous]]
| [[2013Vargas_ParticleQuality]]
| Initial volume in the presence of heterogeneity
| Automatic determination of particle quality
|-  
|-  


| Paper
| Paper
| [[2016Pragier_Graph]]
| [[2014Scheres_Movies]]
| Graph partitioning approach to angular reconstitution
| Beam induced motion correction
|-  
|-  


| Paper
| Paper
| [[2017Greenberg_CommonLines]]
| [[2015Abrishami_Movies]]
| Common lines for reference free ab-initio reconstruction
| Alignment of direct detection device micrographs
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Highres]]
| [[2015Grant_Anisotropic]]
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
| Automatic estimation and correction of anisotropic magnification
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Swarm]]
| [[2015Grant_OptimalExposure]]
| Consensus of several initial volumes by swarm optimization
| Filter movies according to the radiation damage
|-  
|-  


| Paper
| Paper
| [[2019Zehni_Joint]]
| [[2015Rubinstein_Alignment]]
| Continuous angular refinement and reconstruction
| Frame alignment at the level of particle
|-  
|-  


| Paper
| Paper
| [[2019Zehni_Joint]]
| [[2015Spear_DoseCompensation]]
| Continuous angular refinement and reconstruction
| Effect of dose compensation on resolution
|-  
|-  


| Paper
| [[2015Zhao_AnisotropicMagnification]]
| Correction of anisotropic magnification
|-


| Paper
| Conference
| [[2020Sharon_NonUniformKam]]
| [[2016Bajic_Denoising]]
| Reconstruction and angular distribution estimation without angular assignment (reference free)
| Denoising and deconvolution of micrographs
|-  
|-  


| Paper
| Paper
| [[2020Xie_Network]]
| [[2016Jensen_RemovalVesicles]]
| Angular assignment considering a network of assignments
| Removal of vesicles in membrane proteins
|-  
|-  


| Paper
| Paper
| [[2021Jimenez_DeepAlign]]
| [[2016Bhamre_Denoising]]
| Angular alignment using deep learning
| Denoising by 2D covariance estimation
|-  
|-  


| Paper
| Paper
| [[2021Kojima_Preferred]]
| [[2017Berndsen_EMPH]]
| Identification of preferred orientations
| Automated hole masking algorithm
|-  
|-  


| Conference
| Paper
| [[2021Nashed_CryoPoseNet]]
| [[2017McLeod_Zorro]]
| CryoPoseNet: Angular alignment with deep learning
| Movie alignment by Zorro
|-  
|-  


| Conference
| Paper
| [[2021Zhong_CryoDRGN2]]
| [[2017Zheng_MotionCorr2]]
| CryoDRGN2: Angular alignment with deep learning
| Movie alignment by MotionCorr2
|-  
|-  
|}
=== 3D Reconstruction ===
{|


| Paper
| Paper
| [[1972Gilbert_SIRT]]
| [[2018Ouyang_Denoising]]
| Simultaneous Iterative Reconstruction Technique (SIRT)
| Denoising based on geodesic distance
|-  
|-  


| Paper
| Paper
| [[1973Herman_ART]]
| [[2018Wu_ContrastEnhancement]]
| Algebraic Reconstruction Technique (ART)
| Contrast enhancement
|-  
|-  


| Paper
| Paper
| [[1980Kam_SphericalHarmonics]]
| [[2019Zivanov_BayesianBIM]]
| 3D Reconstruction using spherical harmonics
| Bayesian correction of beam induced movement
|-  
|-  


| Paper
| Paper
| [[1984Andersen_SART]]
| [[2020Bepler_TopazDenoise]]
| Simultaneous Algebraic Reconstruction Technique (SART)
| Preprocessing of micrographs for better picking
|-  
|-  


| Paper
| Paper
| [[1986Harauz_FBP]]
| [[2020Chung_2SDR]]
| Exact filters for Filtered Back Projection
| PCA to denoise particles
|-  
|-  


| Chapter
| Paper
| [[1992Radermacher_WBP]]
| [[2020Chung_Prepro]]
| Exact filters for Weighted Back Projection
| Preprocessing of particles for better alignment
|-  
|-  


| Paper
| Conference
| [[1997Zhu_RecCTF]]
| [[2020Huang_SuperResolution]]
| 3D Reconstruction (SIRT like) and simultaneous CTF correction
| Deep learning superresolution combination of frames
|-  
|-  


| Paper
| Paper
| [[1998Boisset_Uneven]]
| [[2020Palovcak_noise2noise]]
| Artifacts in SIRT and WBP under uneven angular distributions
| Noise2noise denoising of micrographs
|-  
|-  


| Paper
| Paper
| [[1998Marabini_ART]]
| [[2020Strelak_FlexAlign]]
| Algebraic Reconstruction Technique with blobs (Xmipp)
| Continuous deformation model for aligning movie frames
|-  
|-  


| Paper
| Conference
| [[2001Sorzano_Uneven]]
| [[2021Fan_Denoising]]
| Free parameter selection under uneven angular distributions
| Particle denoising using vector diffusion maps
|-  
|-  


| Paper
| Paper
| [[2005Sorzano_Parameters]]
| [[2022Heymann_ProgressiveSSNR]]
| Free parameter selection for optimizing multiple tasks
| Progressive SSNR to assess quality and radiation damage
|-  
|-  


| Paper
| Paper
| [[2008Sorzano_Constraints]]
| [[2022Shi_Denoising]]
| Mass, surface, positivity and symmetry constraints for real-space algorithms
| Contrast estimation and denoising in SPA
|-  
|-  


| Paper
| Paper
| [[2009Bilbao_ParallelART]]
| [[2023Huang_ZSSR]]
| Efficient parallelization of ART
| Multiple image super-resolution, upsampling with deep learning
|-  
|-  


| Paper
| Paper
| [[2011Li_GradientFlow]]
| [[2023Marshall_PCA]]
| Regularized 3D Reconstruction by Gradient Flow
| Fast PCA on single particle images
|-  
|-  


| Paper
| Paper
| [[2011Vonesch_Wavelets]]
| [[2023Sharon_Enhancement]]
| Fast wavelet-based 3D reconstruction
| Signal enhancement of SPA particles
|-  
|-  


| Paper
| Paper
| [[2012Gopinath_ShapeRegularization]]
| [[2023Strelak_MovieAlignment]]
| Regularized 3D Reconstruction by Shape information
| Comparison of movie alignment programs
|-  
|-  


| Paper
| Paper
| [[2012Kucukelbir_adaptiveBasis]]
| [[2023Zhang_Denoising]]
| 3D reconstruction in an adaptive basis promoting sparsity
| Single Particle denoising using Deep Convolutional autoencoder and K-means++
|-  
|-  


| Paper
| Paper
| [[2012Sindelar_NoiseReduction]]
| [[2024Li_Subtraction]]
| Optimal noise reduction in 3D reconstructions
| Subtraction of membrane signal in SPA
|-  
|-  
|}
=== 2D Alignment ===
{|


| Paper
| Paper
| [[2013Elmlund H_PRIME]]
| [[1981Frank_Averaging]]
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
| 2D averaging and phase residual
|-  
|-  


| Paper
| Paper
| [[2013Lyumkis_Optimod]]
| [[1982Saxton_Averaging]]
| Construction of initial volumes with Optimod
| 2D averaging using correlation
|-  
|-  


| Paper
| Paper
| [[2013Wang FIRM]]
| [[1998Sigworth_ML2D]]
| Fast 3D reconstruction in Fourier domain
| Maximum likelihood alignment in 2D
|-  
|-  


| Paper
| Paper
| [[2014Kunz_SART_OS]]
| [[2003Cong_FRM2D]]
| Simultaneous ART with OS
| Fast Rotational Matching in 2D
|-  
|-  


| Paper
| Paper
| [[2015Abrishami_Fourier]]
| [[2005Cong_FRM2D]]
| 3D Reconstruction in Fourier space
| Fast Rotational Matching in 2D introduced in a 3D Alignment algorithm
|-  
|-  


| Paper
| Paper
| [[2015Dvornek_SubspaceEM]]
| [[2005Scheres_ML2D]]
| Fast Maximum a posteriori
| Multireference alignment and classification in 2D
|-  
|-  


| Paper
| Paper
| [[2015Moriya_Bayesian]]
| [[2016Aguerrebere_Limits]]
| Bayesian approach to suppress limited angular artifacts
| Fundamental limits of 2D translational alignment
|-  
|-  


| Paper
| Paper
| [[2015Xu_GeometricFlow]]
| [[2010Sorzano_CL2D]]
| Multi-scale geometric flow
| Multireference alignment and classification in 2D
|-  
|-  


| Arxiv
| Conference
| [[2016Ye_Cohomology]]
| [[2017Anoshina_Correlation]]
| Cohomology properties of 3D reconstruction
| New correlation measure for aligning images
|-  
|-  


| Paper
| Paper
| [[2017Punjani_CryoSPARC]]
| [[2019Radermacher_Correlation]]
| CryoSPARC
| On the properties of cross correlation for the alignment of images
|-  
|-  


| Paper
| Paper
| [[2017Punjani_CryoSPARCTheory]]
| [[2020Lederman_representation]]
| Theory related to CryoSPARC
| A representation theory perspective of alignment and classification
|-  
|-  


| Paper
| Paper
| [[2017Sorzano_SurveyIterative]]
| [[2020Marshall_Invariants]]
| Survey of iterative reconstruction methods for EM
| Recovery of an image from its invariants
|-  
|-  


| Paper
| Paper
| [[2018Bartesaghi_Refinement]]
| [[2021Chen_Fast]]
| Refinement of CTF, frame weight and alignment for high resolution reconstruction
| Fast alignment through Power Spectrum
|-  
|-  


| Paper
| Conference
| [[2018Hu_ParticleFilter]]
| [[2021Chung_CryoRALIB]]
| A particle filter framework for 3D reconstruction
| Image alignment acceleration
|-  
|-  


| Conference
| Paper
| [[2018Levin_Kam]]
| [[2021Heimowitz_Centering]]
| Ab initio reconstruction by autocorrelation analysis
| Centering noisy images
|-  
|-  


| Conference
| Conference
| [[2018Michels_RBF]]
| [[2022Bendory_Complexity]]
| Ab-initio reconstruction with radial basis functions
| Computational complexity of multireference image alignment
|-  
|-  


| Paper
| Paper
| [[2018Reboul_Simple]]
| [[2024Bendory_Complexity]]
| Ab initio reconstruction with Simple
| Computational complexity of multireference image alignment
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Highres]]
| [[2024Bai_NUFT]]
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
| 2D Image classification based on the Non-uniform Fourier Transform
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Swarm]]
| [[2025Kapnulin_Outlier]]
| Consensus of several initial volumes by swarm optimization
| 2D Outlier rejection based on radial averages
|-  
|-  


| Paper
| Paper
| [[2018Zhu_Ewald]]
| [[2025Tang_CryoLike]]
| 3D Reconstruction with Ewald sphere correction
| CryoLike: a library for fast image comparison
|-  
|-  
|}
=== 2D Classification and clustering ===
{|


| Paper
| Paper
| [[2019Gomez_Initial]]
| [[1981VanHeel_MSA]]
| Construction of initial models
| Multivariate Statistical Analysis
|-  
|-  


| Master
| Paper
| [[2019Havelkova_Regularization]]
| [[1984VanHeel_MSA]]
| Regularization methods in 3D reconstruction
| Multivariate Statistical Analysis
|-  
|-  


| Paper
| Paper
| [[2019Wilkinson_Scales]]
| [[2005Scheres_ML2D]]
| Combining data acquired at different scales
| Multireference alignment and classification in 2D
|-  
|-  


| Paper
| Paper
| [[2020Alazzawi_Auto]]
| [[2010Sorzano_CL2D]]
| Automatic full processing of micrographs to yield a 3D reconstruction
| Multireference alignment and classification in 2D
|-  
|-  


| Paper
| Paper
| [[2020Pan_TV]]
| [[2011Singer_DiffusionMaps]]
| 3D Reconstruction with total variation regularization
| Classification in 2D based on graph analysis of the projections
|-  
|-  


| Paper
| Paper
| [[2020Punjani_NonUniform]]
| [[2012Yang_ISAC]]
| Non-uniform refinement
| Iterative Stable Alignment and clustering
|-  
|-  


| Paper
| Paper
| [[2020Ramlaul_Sidesplitter]]
| [[2014Sorzano_Outlier]]
| Local filtering along the reconstruction iterations
| Outlier detection in 2D classifications.
|-  
|-  


| Paper
| Paper
| [[2020Xie_Automatic]]
| [[2014Zhao_Aspire]]
| Automatic 3D reconstruction from projections
| Fast classification based on rotational invariants and vector diffusion maps
|-  
|-  


| Conference
| Paper
| [[2020Venkatakrishnan_MBIR]]
| [[2015Huang_Robust]]
| Model based image reconstruction
| Robust w-estimators of 2D classes
|-  
|-  


| Paper
| Paper
| [[2020Zhou_AutomaticSelection]]
| [[2016Kimanius_Accelerated]]
| Automatic selection of particles for 3D reconstruction
| GPU Accelerated image classification and high-resolution refinement
|-  
|-  


| Paper
| Paper
| [[2021Abrishami_Localized]]
| [[2016Reboul_Stochastic]]
| Localized reconstruction in scipion expedites the analysis of symmetry mismatches in Cryo-EM data
| Stochastic Hill Climbing for calculating 2D classes
|-  
|-  


| Paper
| Conference
| [[2021Gupta_CryoGAN]]
| [[2017Bhamre_Mahalanobis]]
| 3D Reconstruction via Generative Adversarial Learning
| 2D classification using Mahalanobis distance
|-  
|-  


| Paper
| Paper
| [[2021Luo_Opus]]
| [[2017Wu_GTM]]
| 3D Reconstruction with a sparse and smoothness constraint
| 2D classification using Generative Topographic Mapping
|-  
|-  


| Paper
| Conference
| [[2021Kimanius_PriorKnowledge]]
| [[2018Boumal_SinglePass]]
| Incorporation of prior knowledge during 3D reconstruction
| Single pass classification
|-
 
| Conference
| [[2018Shuo_Network]]
| 2D Clustering by network metrics
|-  
|-  


| Paper
| Paper
| [[2021Sorzano_Uneven]]
| [[2020Ma_RotationInvariant]]
| Algorithmic robustness to uneven angular distributions
| 2D heterogeneity determination by rotation invariant features
|-  
|-  


|}
| Conference
| [[2020Miolane_VAEGAN]]
| 2D Analysis by deep learning
|-


=== 3D Heterogeneity ===
| Conference
 
| [[2021Rao_Wasserstein]]
{|
| Wasserstein K-Means for Clustering Tomographic Projections
|-


| Paper
| Paper
| [[2004White_Size]]
| [[2022Vilela_Feret]]
| Heterogeneity classification of differently sized images
| 2D heterogeneity detection through Feret signatures
|-  
|-  


| Paper
| Paper
| [[2006Penczek_Bootstrap]]
| [[2022Wang_Spectral]]
| 3D heterogeneity through bootstrap
| 2D classification with spectral clustering
|-  
|-  


| Paper
| Paper
| [[2007Leschziner_Review]]
| [[2022Zhang_DRVAE]]
| Review of 3D heterogeneity handling algorithms
| 2D classification with deep learning and K-means++
|-  
|-  


| Paper
| Paper
| [[2007Scheres_ML3D]]
| [[2023Chen_Joint]]
| Maximum Likelihood alignment and classification in 3D
| 2D classification with deep learning and joint unsupervised difference learning
|-  
|-  


| Paper
| Conference
| [[2008Herman_Graph]]
| [[2023Weiss_Noise]]
| Classification by graph partitioning
| Identifying non-particles with probabilistic PCA
|-  
|-  


| Paper
| Paper
| [[2009Spahn_Bootstrap]]
| [[2024Tang_SimCryoCluster]]
| 3D heterogeneity through bootstrap
| SimCryoCluster: 2D classification in SPA using a deep clustering method
|-  
|-  


| Paper
| Paper
| [[2010Elmlund_AbInitio]]
| [[2025Bai_NUDFT]]
| Solving the initial volume problem with multiple conformations
| 2D Classification in SPA using the Non-uniform DFT
|-  
|-  


| Paper
|}
| [[2010Shatsky_MultiVariate]]
 
| Multivariate Statistical Analysis
=== 3D Alignment ===
|-
 
{|


| Paper
| Paper
| [[2012Scheres_Bayesian]]
| [[1980Kam_AutoCorrelation]]
| A Bayesian view on cryo-EM structure determination
| Reconstruction without angular assignment from autocorrelation function (reference free)
|-  
|-  


| Paper
| Paper
| [[2012Zheng_Covariance]]
| [[1986Goncharov_CommonLines]]
| Estimation of the volume covariance
| Angular assignment using common lines (reference free)
|-  
|-  


| Paper
| Paper
| [[2013Wang_MLVariance]]
| [[1987VanHeel_CommonLines]]
| Maximum Likelihood estimate of the map variance
| Angular assignment using common lines (reference free)
|-  
|-  


| Paper
| Paper
| [[2013Lyumkis D_FREALIGN]]
| [[1988Provencher_Simultaneous]]
| Likelihood-based classification of cryo-EM images using FREALIGN.
| Simultaneaous alignment and reconstruction
|-
|-  


| Paper
| Paper
| [[2014Chen_Migration]]
| [[1988Radermacher_RCT]]
| Particle migration analysis in 3D classification
| Random Conical Tilt and Single axis tilt
|-  
|-  


| Paper
| Paper
| [[2014Dashti_Brownian]]
| [[1988Vogel_Simultaneous]]
| Continuous heterogeneity through Brownian trajectories
| Simultaneaous alignment and reconstruction
|-  
|-  


| Paper
| Paper
| [[2014Schwander_manifold]]
| [[1990Gelfand_Moments]]
| Continuous heterogeneity through Manifold Analysis
| Angular assignment using moments (reference free)
|-  
|-  


| Paper
| Paper
| [[2014Jin_NMA]]
| [[1990Goncharov_Moments]]
| Continuous heterogeneity through Normal Mode Analysis
| Angular assignment using moments (reference free)
|-  
|-  


| Paper
| Paper
| [[2015Anden_Covariance]]
| [[1990Harauz_Quaternions]]
| 3D Covariance matrix estimation for heterogeneity
| Use of quaternions to represent rotations
|-  
|-  


| Paper
| Paper
| [[2015Bai_Focused]]
| [[1994Penczek_Real]]
| Focused classification
| Angular assignment using projection matching in real space
|-  
|-  


| Paper
| Paper
| [[2015Katsevich_Covariance]]
| [[1994Radermacher_Radon]]
| 3D Covariance matrix estimation for heterogeneity
| Angular assignment in Radon space
|-  
|-  


| Paper
| Paper
| [[2015Klaholz_MRA]]
| [[1996Penczek_CommonLines]]
| Multivariate Statistical Analysis of Jackknife and Bootstrapping on random subsets
| Angular assignment using common lines (reference free)
|-  
|-  


| Paper
| Paper
| [[2015Liao_Covariance]]
| [[2003Rosenthal_DPR]]
| Estimation of the 3D covariance from 2D projections
| Angular assignment using DPR
|-  
|-  


| Paper
| Paper
| [[2015Tagare_Direct]]
| [[2004Sorzano_Wavelet]]
| Direct reconstruction of PCA components
| Angular assignment in the wavelet space.
|-  
|-  


| Paper
| Paper
| [[2016Gong_Mechanical]]
| [[2005Jonic_Splines]]
| Mechanical model for macromolecules
| Angular assignment in Fourier space using spline interpolation.
|-  
|-  


| Paper
| Paper
| [[2016Rawson_Movement]]
| [[2005Yang_Simultaneous]]
| Movement and flexibility
| Simultaneaous alignment and reconstruction
|-  
|-  


| Paper
| Paper
| [[2016Shan_Multibody]]
| [[2006Ogura_SimulatedAnnealing]]
| Multibody refinement
| Angular asignment by simulated annealing
|-  
|-  


| Paper
| Paper
| [[2016Sorzano_StructMap]]
| [[2007Grigorieff_Continuous]]
| Sorting a discrete set of conformational states
| Continuous angular assignment in Fourier space
|-  
|-  


| Paper
| Paper
| [[2016Sorzano_Strain]]
| [[2010Jaitly_Bayesian]]
| Calculate local stretches, strains and rotations from two conformational states
| Angular assignment by a Bayesian method and annealing
|-  
|-


| Paper
| Paper
| [[2017Punjani_CryoSPARC]]
| [[2010Sanz_Random]]
| CryoSPARC
| Random model method
|-  
|-


| Paper
| Paper
| [[2017Schillbach_Warpcraft]]
| [[2010Singer_Voting]]
| Warpcraft: 3D Reconstruction in the presence of continuous heterogeneity
| Detecting consistent common lines by voting (reference free)
|-  
|-


| Paper
| Paper
| [[2018Anden_Covariance]]
| [[2011Singer_SDP]]
| Structural Variability from Noisy Tomographic Projections
| Angular assignment by semidefinite programming and eigenvectors (reference free)
|-  
|-


| Paper
| Paper
| [[2018Haselbach_FreeEnergy]]
| [[2012Giannakis_Scattering]]
| Analysis of the free energy landscape through PCA
| Construction of an initial volume, reference free, by graph analysis of the projections
|-  
|-


| Paper
| Paper
| [[2018Nakane_MultiBody]]
| [[2012Shkolnisky_Sync]]
| Structural Variability through multi-body refinement
| Angular assignment by synchronization of rotations (reference free)
|-  
|-


| Paper
| Paper
| [[2019Serna_Review]]
| [[2013Elmlund H_PRIME]]
| Review of classification tools
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
|-  
|-  


| Paper
| Paper
| [[2018Solernou_FFEA]]
| [[2013Wang_LUD]]
| Fluctuating Finite Element Analysis, continuum approach to Molecular Dynamics
| Angular assignment by least unsquared deviations (reference free)
|-
 
| Paper
| [[2014Vargas_RANSAC]]
|  Initial model using RANSAC (reference free)
|-
 
| Paper
| [[2015Joubert_Pseudoatoms]]
| Initial model based on pseudo-atoms
|-  
|-  


| Paper
| Paper
| [[2019Sorzano_Review]]
| [[2015Singer_Kam]]
| Review of continuous heterogeneity biophysics
| Reconstruction without angular assignment from autocorrelation function (reference free)
|-  
|-  


| Paper
| Paper
| [[2019Zhang_Local]]
| [[2015Sorzano_Significant]]
| Local variability and covariance
| Statistical approach to the initial volume estimation (reconstruct significant)
|-  
|-  


| Paper
| Paper
| [[2020Dashti_Landscape]]
| [[2016Cossio_BayesianGPU]]
| Retrieving functional pathways from single particle snapshots
| GPU implementation of the Bayesian 3D reconstruction approach
|-  
|-  


| Conference
| Conference
| [[2020Gupta_MultiCryoGAN]]
| [[2016Michels_Heterogeneous]]
| Reconstruction of continuously heterogeneous structures with adversarial networks
| Initial volume in the presence of heterogeneity
|-  
|-  


| Paper
| Paper
| [[2020Harastani_NMA]]
| [[2016Pragier_Graph]]
| Using Scipion for analyzing local heterogeneity with normal modes
| Graph partitioning approach to angular reconstitution
|-  
|-  


| Paper
| Paper
| [[2020Maji_Propagation]]
| [[2017Greenberg_CommonLines]]
| Propagation of conformational coordinates across angular space
| Common lines for reference free ab-initio reconstruction
|-  
|-  


| Paper
| Paper
| [[2020Moscovich_DiffusionMaps]]
| [[2018Sorzano_Highres]]
| Heterogeneity analysis by diffusion maps and spectral volumes
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
|-  
|-  


| Paper
| Paper
| [[2020Seitz_Polaris]]
| [[2018Sorzano_Swarm]]
| Analysis of energy landscapes to find minimal action paths
| Consensus of several initial volumes by swarm optimization
|-  
|-  


| Conference
| Paper
| [[2020Zhong_CryoDRGN]]
| [[2019Zehni_Joint]]
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
| Continuous angular refinement and reconstruction
|-  
|-  


| Paper
| Paper
| [[2020Verbeke_Separation]]
| [[2019Zehni_Joint]]
| Heterogeneity analysis by comparing common lines
| Continuous angular refinement and reconstruction
|-  
|-  


| Paper
| Paper
| [[2021Chen_GM]]
| [[2020Sharon_NonUniformKam]]
| Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability
| Reconstruction and angular distribution estimation without angular assignment (reference free)
|-  
|-  


| Paper
| Paper
| [[2021Giraldo_cryoBIFE]]
| [[2020Xie_Network]]
| A Bayesian approach to extracting free‑energy profiles
| Angular assignment considering a network of assignments
|-  
|-  


| Conference
| Paper
| [[2021Hamitouche_NMADL]]
| [[2021Jimenez_DeepAlign]]
| Continuous heterogeneity analysis through normal modes and deep learning
| Angular alignment using deep learning
|-  
|-  


| Paper
| Paper
| [[2021Herreros_Zernikes3D]]
| [[2021Kojima_Preferred]]
| Continuous heterogeneity analysis through Zernikes 3D
| Identification of preferred orientations
|-  
|-  


| Paper
| Conference
| [[2021Kazemi_Enrich]]
| [[2021Nashed_CryoPoseNet]]
| ENRICH: A fast method to improve the quality of flexible macromolecular reconstructions
| CryoPoseNet: Angular alignment with deep learning
|-  
|-  


| Paper
| Conference
| [[2021Matsumoto_DEFmap]]
| [[2021Zhong_CryoDRGN2]]
| Prediction of RMSF of Molecular Dynamics from a CryoEM map using deep learning
| CryoDRGN2: Angular alignment with deep learning
|-  
|-  


| Chapter
| Conference
| [[2021Nakasako_Landscape]]
| [[2022Levy_CryoAI]]
| Estimation of free-energy landscape from images
| CryoAI: Angular assignment through neural network
|-  
|-  


| Paper
| Paper
| [[2021Punjani_3DVA]]
| [[2022Lian_Neural]]
| 3D Variability analysis from images
| Angular assignment through neural network
|-  
|-  


| Paper
| Paper
| [[2021Sorzano_PCA]]
| [[2022Lu_SphericalEmbeddings]]
| PCA is limited to low-resolution
| Angular assignment through common lines and spherical embeddings
|-  
|-  


| Paper
| Paper
| [[2021Zhong_CryoDRGN]]
| [[2022Wang_Thunder]]
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
| Angular assignment implementation in GPU
|-
 
| Conference
| [[2023Cesa_Alignment]]
| 3D alignment based on deep learning and equivariant representations
|-  
|-  


| Paper
| Paper
| [[2022Ecoffet_MorphOT]]
| [[2023Harpaz_Alignment]]
| More physically plausible morphing between two states
| Fast alignment of two maps using common lines
|-  
|-  


| Paper
| Paper
| [[2022Gomez_Hierarchical]]
| [[2023Ling_Synch]]
| Hierarchical classification of particles
| Synchronization of projection directions
|-  
|-  


|}
| Paper
 
| [[2023Rangan_Fast]]
=== Validation ===
| Fast angular assignment using Fourier-Bessel
 
|-
{|


| Paper
| Paper
| [[2008Stagg_TestBed]]
| [[2023Riahi_Transport]]
| Effect of voltage, dosis, number of particles and Euler jumps on resolution
| Alignment of two 3D maps using Wasserstein's distance
|-  
|-  


| Paper
| Paper
| [[2011Henderson]]
| [[2024Chung_CryoForum]]
| Tilt Validation
| CryoForum: Angular assignment with uncertainty estimation using neural networks
|-  
|-  


| Paper
| Paper
| [[2011Read]]
| [[2024Muller_Common]]
| Validation of PDBs
| Initial volume in the presence of heterogeneity using common lines
|-  
|-  


| Paper
| Paper
| [[2012Henderson]]
| [[2024Nottelet_Feret]]
| EM Map Validation
| Feret signature to detect preferred orientations and misclassified images
|-  
|-  


| Paper
| Paper
| [[2013Cossio_Bayesian]]
| [[2024Sanchez_Cesped]]
| EM Map Validation in a probabilistic setting
| CESPED: A benchmark for supervised particle pose estimation
|-  
|-  


| Paper
| Conference
| [[2013Chen_NoiseSubstitution]]
| [[2024Shekarforoush_CryoSPIN]]
| Noise substitution at high resolution for measuring overfitting
| CryoSpin: Semi-amortized image alignment using deep learning
|-  
|-  


| Paper
| Paper
| [[2013Ludtke_Validation]]
| [[2024Singer_Wasserstein]]
| Structural validation, example of the Calcium release channel
| Alignment of two 3D maps using Wasserstein's distance
|-  
|-  


| Paper
| Paper
| [[2013Murray_Validation]]
| [[2024Titarenko_optimal]]
| Validation of a 3DEM structure through a particular example
| Optimal 3D angular sampling
|-  
|-  


| Paper
| Paper
| [[2014Russo_StatisticalSignificance]]
| [[2024Wang_CommonLines]]
| EM Map Validation through the statistical significance of the tilt-pair angular assignment
| 3D Alignment by common lines
|-  
|-  


| Paper
| Paper
| [[2014Stagg_Reslog]]
| [[2024Zhang_Kam]]
| EM Map Validation through the resolution evolution with the number of particles
| Distance between maps without aligning them
|-  
|-  
|}
=== 3D Reconstruction ===
{|


| Paper
| Paper
| [[2014Wasilewski_Tilt]]
| [[1972Gilbert_SIRT]]
| Web implementation of the tilt pair validation
| Simultaneous Iterative Reconstruction Technique (SIRT)
|-  
|-  


| Paper
| Paper
| [[2015Heymann_Alignability]]
| [[1973Herman_ART]]
| EM Map Validation through the resolution of reconstructions from particles and noise
| Algebraic Reconstruction Technique (ART)
|-  
|-  


| Paper
| Paper
| [[2015Oliveira_FreqLimited]]
| [[1980Kam_SphericalHarmonics]]
| Comparison of gold standard and frequency limited optimization
| 3D Reconstruction using spherical harmonics
|-  
|-  


| Paper
| Paper
| [[2015Rosenthal_Review]]
| [[1984Andersen_SART]]
| Review of validation methods
| Simultaneous Algebraic Reconstruction Technique (SART)
|-  
|-  


| Paper
| Paper
| [[2015Wriggers_Secondary]]
| [[1986Harauz_FBP]]
| Validation by secondary structure
| Exact filters for Filtered Back Projection
|-  
|-  


| Paper
| Chapter
| [[2016Degiacomi_IM]]
| [[1992Radermacher_WBP]]
| Comparison of Ion Mobility data and EM volumes
| Exact filters for Weighted Back Projection
|-  
|-  


| Paper
| Paper
| [[2016Kim_SAXS]]
| [[1997Zhu_RecCTF]]
| Comparison of SAXS data and EM projections
| 3D Reconstruction (SIRT like) and simultaneous CTF correction
|-  
|-  


| Paper
| Paper
| [[2016Rosenthal_Review]]
| [[1998Boisset_Uneven]]
| Review of validation methods
| Artifacts in SIRT and WBP under uneven angular distributions
|-  
|-  


| Paper
| Paper
| [[2016Vargas_Alignability]]
| [[1998Marabini_ART]]
| Validation by studying the tendency of an angular assignment to cluster in the projection space
| Algebraic Reconstruction Technique with blobs (Xmipp)
|-  
|-  


| Paper
| Paper
| [[2017Monroe_PDBRefinement]]
| [[2001Sorzano_Uneven]]
| Validation by comparison to a refined PDB
| Free parameter selection under uneven angular distributions
|-  
|-  


| Paper
| Paper
| [[2018Afonine_Phenix]]
| [[2005Sorzano_Parameters]]
| Tools in Phenix for the validation of EM maps
| Free parameter selection for optimizing multiple tasks
|-  
|-  


| Paper
| Paper
| [[2018Heymann_Bsoft]]
| [[2008Sorzano_Constraints]]
| Map validation using Bsoft
| Mass, surface, positivity and symmetry constraints for real-space algorithms
|-  
|-  


| Paper
| Paper
| [[2018Heymann_Challenge]]
| [[2009Bilbao_ParallelART]]
| A summary of the assessments of the 3D Map Challenge
| Efficient parallelization of ART
|-  
|-  


| Paper
| Paper
| [[2018Jonic_Gaussian]]
| [[2011Li_GradientFlow]]
| Assessment of sets of volumes by pseudoatomic structures
| Regularized 3D Reconstruction by Gradient Flow
|-  
|-  


| Paper
| Paper
| [[2018Naydenova_AngularDistribution]]
| [[2011Vonesch_Wavelets]]
| Evaluating the angular distribution of a 3D reconstruction
| Fast wavelet-based 3D reconstruction  
|-  
|-  


| Paper
| Paper
| [[2018Pages_Symmetry]]
| [[2012Gopinath_ShapeRegularization]]
| Looking for a symmetry axis in a PDB
| Regularized 3D Reconstruction by Shape information
|-  
|-  


| Paper
| Paper
| [[2018Pintilie_SSE]]
| [[2012Kucukelbir_adaptiveBasis]]
| Evaluating the quality of SSE and side chains
| 3D reconstruction in an adaptive basis promoting sparsity
|-  
|-  


| Paper
| Paper
| [[2019Herzik_Multimodel]]
| [[2012Sindelar_NoiseReduction]]
| Local and global quality by multi-model fitting
| Optimal noise reduction in 3D reconstructions
|-  
|-  


| Paper
| Paper
| [[2020Chen_Atomic]]
| [[2013Elmlund H_PRIME]]
| Validation of the atomic models derived from CryoEM
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
|-  
|-  


| Paper
| Paper
| [[2020Cossio_CrossValidation]]
| [[2013Lyumkis_Optimod]]
| Need for cross validation
| Construction of initial volumes with Optimod
|-  
|-  


| Paper
| Paper
| [[2020Ortiz_CrossValidation]]
| [[2013Wang FIRM]]
| Cross validation for SPA
| Fast 3D reconstruction in Fourier domain
|-  
|-  


| Paper
| Paper
| [[2020Sazzed_helices]]
| [[2014Kunz_SART_OS]]
| Validation of helix quality
| Simultaneous ART with OS
|-  
|-  


| Paper
| Paper
| [[2020Stojkovic_PTM]]
| [[2015Abrishami_Fourier]]
| Validation of post-translational modifications
| 3D Reconstruction in Fourier space
|-  
|-  


| Paper
| Paper
| [[2020Tiwari_PixelSize]]
| [[2015Dvornek_SubspaceEM]]
| Fine determination of the pixel size
| Fast Maximum a posteriori
|-  
|-  


| Paper
| Paper
| [[2021Mendez_Graph]]
| [[2015Moriya_Bayesian]]
| Identification of incorrectly oriented particles
| Bayesian approach to suppress limited angular artifacts
|-  
|-  


| Paper
| Paper
| [[2021Pintilie_Validation]]
| [[2015Xu_GeometricFlow]]
| Review of map validation approaches
| Multi-scale geometric flow
|-
 
| Arxiv
| [[2016Ye_Cohomology]]
| Cohomology properties of 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2021Olek_FDR]]
| [[2017Barnett_Marching]]
| Cryo-EM Map–Based Model Validation Using the False Discovery Rate Approach
| Initial volume through frequency marching
|-  
|-  


|}
| Paper
 
| [[2017Punjani_CryoSPARC]]
=== Resolution ===
| CryoSPARC
 
|-
{|


| Paper
| Paper
| [[1986Harauz_FBP]]
| [[2017Punjani_CryoSPARCTheory]]
| Fourier Shell Correlation
| Theory related to CryoSPARC
|-  
|-  


| Paper
| Paper
| [[1987Unser_SSNR]]
| [[2017Sorzano_SurveyIterative]]
| 2D Spectral Signal to Noise Ratio
| Survey of iterative reconstruction methods for EM
|-  
|-  


| Paper
| Paper
| [[2002Penczek_SSNR]]
| [[2018Bartesaghi_Refinement]]
| 3D Spectral Signal to Noise Ratio for Fourier based algorithms
| Refinement of CTF, frame weight and alignment for high resolution reconstruction
|-  
|-  


| Paper
| Paper
| [[2003Rosenthal_DPR]]
| [[2018Hu_ParticleFilter]]
| Review of the FSC and establishment of a new threshold
| A particle filter framework for 3D reconstruction
|-  
|-  


| Paper
| Conference
| [[2005Unser_SSNR]]
| [[2018Levin_Kam]]
| 3D Spectral Signal to Noise Ratio for any kind of algorithms
| Ab initio reconstruction by autocorrelation analysis
|-  
|-  


| Paper
| Conference
| [[2005VanHeel_FSC]]
| [[2018Michels_RBF]]
| Establishment of a new threshold for FSC
| Ab-initio reconstruction with radial basis functions
|-  
|-  


| Paper
| Paper
| [[2007Sousa_AbInitio]]
| [[2018Reboul_Simple]]
| Resolution measurement on neighbour Fourier voxels
| Ab initio reconstruction with Simple
|-  
|-  


| Paper
| Paper
| [[2014Kucukelbir_Local]]
| [[2018Sorzano_Highres]]
| Quantifying the local resolution of cryo-EM density maps
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
|-  
|-  


| Paper
| Paper
| [[2016Pintilie_Probabilistic]]
| [[2018Sorzano_Swarm]]
| Probabilistic models and resolution
| Consensus of several initial volumes by swarm optimization
|-  
|-  


| Paper
| Paper
| [[2017Sorzano_FourierProperties]]
| [[2018Zhu_Ewald]]
| Statistical properties of resolution measures defined in Fourier space
| 3D Reconstruction with Ewald sphere correction
|-
 
| Conference
| [[2018Avramov_DeepLearning]]
| Deep learning classification of volumes into low, medium and high resolution
|-  
|-  


| Paper
| Paper
| [[2018Carugo_BFactors]]
| [[2019Gomez_Initial]]
| How large can B-factors be in protein crystals
| Construction of initial models
|-  
|-  


| Conference
| Master
| [[2018Kim_FourierError]]
| [[2019Havelkova_Regularization]]
| Comparison between a gold standard and a reconstruction
| Regularization methods in 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2018Rupp_Problems]]
| [[2019Wilkinson_Scales]]
| Problems of resolution as a proxy number for map quality
| Combining data acquired at different scales
|-  
|-  


| Paper
| Paper
| [[2018Vilas_MonoRes]]
| [[2020Alazzawi_Auto]]
| Local resolution by monogenic signals
| Automatic full processing of micrographs to yield a 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2018Yang_Multiscale]]
| [[2020Pan_TV]]
| Resolution from a multiscale spectral analysis
| 3D Reconstruction with total variation regularization
|-  
|-  


| Paper
| Paper
| [[2019Avramov_DeepLearning]]
| [[2020Punjani_NonUniform]]
| Deep learning classification of volumes into low, medium and high resolution
| Non-uniform refinement
|-  
|-  


| Paper
| Paper
| [[2019Heymann_Statistics]]
| [[2020Ramlaul_Sidesplitter]]
| SNR, FSC, and related statistics
| Local filtering along the reconstruction iterations
|-  
|-  


| Paper
| Paper
| [[2019Ramirez_DeepRes]]
| [[2020Xie_Automatic]]
| Resolution determination by deep learning
| Automatic 3D reconstruction from projections
|-  
|-  


| Paper
| Conference
| [[2020Baldwin_Lyumkis_SCF]]
| [[2020Venkatakrishnan_MBIR]]
| Resolution attenuation through non-uniform Fourier sampling
| Model based image reconstruction
|-  
|-  


| Paper
| Paper
| [[2020Beckers_Permutation]]
| [[2020Zhou_AutomaticSelection]]
| Permutation tests for the FSC
| Automatic selection of particles for 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2020Penczek_mFSC]]
| [[2021Abrishami_Localized]]
| Modified FSC to avoid mask induced artifacts
| Localized reconstruction in scipion expedites the analysis of symmetry mismatches in Cryo-EM data
|-  
|-  


| Paper
| Paper
| [[2020Vilas_MonoDir]]
| [[2021Gupta_CryoGAN]]
| Local and directional resolution
| 3D Reconstruction via Generative Adversarial Learning
|-  
|-  


|}
| Paper
| [[2021Luo_Opus]]
| 3D Reconstruction with a sparse and smoothness constraint
|-


=== Sharpening of high resolution information ===
{|
| Paper
| Paper
| [[2003Rosenthal_DPR]]
| [[2021Kimanius_PriorKnowledge]]
| Contrast restoration and map sharpening
| Incorporation of prior knowledge during 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2008Fernandez_Bfactor]]
| [[2021Sorzano_Uneven]]
| Bfactor determination and restoration
| Algorithmic robustness to uneven angular distributions
|-  
|-  


| Paper
| Paper
| [[2013Fiddy_SaxtonAlgorithm]]
| [[2022Havelkova_regularization]]
| Phase retrieval or extension
| Regularization of iterative reconstruction algorithms
|-  
|-  


| Paper
| Conference
| [[2014Kishchenko_SphericalDeconvolution]]
| [[2022Kimanius_Sparse]]
| Spherical deconvolution
| Sparse Fourier backpropagation
|-  
|-  


| Paper
| Paper
| [[2015Spiegel_VISDEM]]
| [[2022Lan_RCT]]
| Visualization improvement by the use of pseudoatomic profiles
| Random Conical Tilt without picking
|-  
|-  


| Paper
| Paper
| [[2016Jonic_Pseudoatoms]]
| [[2023Bendory_Autocorrelation]]
| Approximation with pseudoatoms
| Initial volume through autocorrelation analysis with sparsity constraints
|-  
|-  


| Paper
| Paper
| [[2016Jonic_Denoising]]
| [[2023Geva_AbInitio]]
| Denoising and high-frequency boosting by pseudoatom approximation
| Initial volume through common lines for tetahedral and octahedral symmetry
|-  
|-  


| Paper
| Paper
| [[2017Jakobi_LocScale]]
| [[2023Herreros_ZART]]
| Sharpening based on an atomic model
| Correction of continuous heterogeneity during the 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2019Ramlaul_Filtering]]
| [[2023Rangan_AbInitio]]
| Local agreement filtering (denoising)
| Robust ab initio reconstruction
|-  
|-  


| Conference
| Paper
| [[2020Mullick_SuperResolution]]
| [[2023Zhu_CryoSieve]]
| Superresolution from a map
| CryoSieve: Selection of the best particles to reconstruct
|-  
|-  


| Paper
| Paper
| [[2020Ramirez_LocalDeblur]]
| [[2024Aiyer_Workflow]]
| Local deblur (local Wiener filter)
| Workflow for the reconstruction of tilted samples
|-  
|-  


| Paper
| Paper
| [[2020Terwilliger_density]]
| [[2024Huang_CryoNefen]]
| Density modification of CryoEM maps
| 3D reconstruction in real space with neural networks
|-  
|-  


| Paper
| Paper
| [[2020Vilas_Bfactor]]
| [[2024Liu_kinetic]]
| Global B-factor correction does not represent macromolecules
| A kinetic model for the resolution of the initial model using common lines
|-  
|-  


| Paper
| Paper
| [[2021Beckers_Interpretation]]
| [[2024Suder_Workflow]]
| Improvements from the raw reconstruction to a structure to model
| Workflow for the reconstruction of subparticles in highly symmetrical objects
|-
 
| Paper
| [[2024Zhu_SIRM]]
| Reconstruction strategy and weights to fight preferred orientations
|-  
|-  


| Paper
| Paper
| [[2021Kaur_LocSpiral]]
| [[2025Liu_SpIsonet]]
| LocSpiral, LocBsharpen, LocBfactor
| Deep learning approach to fighting preferential orientations during 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2021Fernandez_Adjustment]]
| [[2025Singh_Mismatch]]
| Map adjustment for subtraction, consensus and sharpening
| Image processing workflow to address particles with symmetry mismatches
|-  
|-  


| Paper
| Paper
| [[2021Sanchez_DeepEMhancer]]
| [[2025Van_Probabilistic]]
| Deep learning algorithm for volume restoration
| Multireference initial volume reconstruction in SPA
|-  
|-  


| Paper
| Paper
| [[2022Vargas_tubular]]
| [[2025Woollard_InstaMap]]
| Map enhancement by multiscale tubular filter
| InstaMap: 3D reconstruction using neural networks
|-  
|-  


|}
|}


=== CTF estimation and restoration ===
=== 3D Heterogeneity ===


{|
{|


| Paper
| Paper
| [[1982Schiske_Correction]]
| [[2004White_Size]]
| CTF correction for tilted objects
| Heterogeneity classification of differently sized images
|-  
|-  


| Paper
| Paper
| [[1988Toyoshima_Model]]
| [[2006Penczek_Bootstrap]]
| CTF estimation
| 3D heterogeneity through bootstrap
|-  
|-  


| Paper
| Paper
| [[1995Frank_Wiener]]
| [[2007Leschziner_Review]]
| CTF correction using Wiener filter
| Review of 3D heterogeneity handling algorithms
|-  
|-  


| Paper
| Paper
| [[1996Skoglund_MaxEnt]]
| [[2007Scheres_ML3D]]
| CTF correction with Maximum Entropy
| Maximum Likelihood alignment and classification in 3D
|-  
|-  


| Paper
| Paper
| [[1996Zhou_Model]]
| [[2008Herman_Graph]]
| CTF model and user interface for manual fitting
| Classification by graph partitioning
|-  
|-  


| Paper
| Paper
| [[1997Fernandez_AR]]
| [[2009Spahn_Bootstrap]]
| PSD estimation using periodogram averaging and AR models
| 3D heterogeneity through bootstrap
|-  
|-  


| Paper
| Paper
| [[1997Penczek_Wiener]]
| [[2010Elmlund_AbInitio]]
| CTF correction using Wiener filter
| Solving the initial volume problem with multiple conformations
|-  
|-  


| Paper
| Paper
| [[1997Stark_Deconvolution]]
| [[2010Shatsky_MultiVariate]]
| CTF correction using deconvolution
| Multivariate Statistical Analysis
|-  
|-  


| Paper
| Paper
| [[1997Zhu_RecCTF]]
| [[2012Scheres_Bayesian]]
| CTF correction and reconstruction
| A Bayesian view on cryo-EM structure determination
|-  
|-  


| Paper
| Paper
| [[2000DeRosier_EwaldCorrection]]
| [[2012Zheng_Covariance]]
| CTF correction considering the Ewald sphere
| Estimation of the volume covariance
|-  
|-  


| Paper
| Paper
| [[2000Jensen_TiltedCorrection]]
| [[2013Wang_MLVariance]]
| CTF correction considering tilt in backprojection
| Maximum Likelihood estimate of the map variance
|-  
|-  


| Paper
| Paper
| [[2001Saad_CTFEstimate]]
| [[2013Lyumkis D_FREALIGN]]
| CTF estimation
| Likelihood-based classification of cryo-EM images using FREALIGN.
|-  
|-


| Paper
| Paper
| [[2003Huang_CTFEstimate]]
| [[2014Chen_Migration]]
| CTF estimation
| Particle migration analysis in 3D classification
|-  
|-  


| Paper
| Paper
| [[2003Mindell_CTFTILT]]
| [[2014Dashti_Brownian]]
| CTF estimation for tilted micrographs
| Continuous heterogeneity through Brownian trajectories
|-  
|-  


| Paper
| Paper
| [[2003Sander_MSA]]
| [[2014Schwander_manifold]]
| CTF estimation through MSA classification of PSDs
| Continuous heterogeneity through Manifold Analysis
|-  
|-  


| Paper
| Paper
| [[2003Velazquez_ARMA]]
| [[2014Jin_NMA]]
| PSD and CTF estimation using ARMA models
| HEMNMA: Continuous heterogeneity through Normal Mode Analysis
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_IDR]]
| [[2015Anden_Covariance]]
| CTF restoration and reconstruction with Iterative Data Refinement
| 3D Covariance matrix estimation for heterogeneity
|-  
|-  


| Conference
| Paper
| [[2004Wan_CTF]]
| [[2015Bai_Focused]]
| Spatially variant CTF
| Focused classification
|-  
|-  


| Paper
| Paper
| [[2004Zubelli_Chahine]]
| [[2015Katsevich_Covariance]]
| CTF restoration and reconstruction with Chahine's multiplicative method
| 3D Covariance matrix estimation for heterogeneity
|-  
|-  


| Conference
| Paper
| [[2005Dubowy_SpaceVariant]]
| [[2015Klaholz_MRA]]
| CTF correction when this is space variant
| Multivariate Statistical Analysis of Jackknife and Bootstrapping on random subsets
|-  
|-  


| Paper
| Paper
| [[2005Mallick_ACE]]
| [[2015Liao_Covariance]]
| CTF estimation
| Estimation of the 3D covariance from 2D projections
|-  
|-  


| Paper
| Paper
| [[2006Wolf_Ewald]]
| [[2015Tagare_Direct]]
| CTF correction considering Ewald sphere
| Direct reconstruction of PCA components
|-  
|-  


| Paper
| Paper
| [[2007Jonic_EnhancedPSD]]
| [[2016Gong_Mechanical]]
| PSD enhancement for better identification of Thon rings; Vitreous ice diffracts in Thon rings
| Mechanical model for macromolecules
|-  
|-  


| Paper
| Paper
| [[2007Philippsen_Model]]
| [[2016Rawson_Movement]]
| CTF Model for tilted specimens
| Movement and flexibility
|-  
|-  


| Paper
| Paper
| [[2007Sorzano_CTF]]
| [[2016Shan_Multibody]]
| CTF estimation using enhanced PSDs
| Multibody refinement
|-  
|-  


| Paper
| Paper
| [[2009Sorzano_Sensitivity]]
| [[2016Sorzano_StructMap]]
| Error sensitivity of the CTF models, non-uniqueness of the CTF parameters
| Sorting a discrete set of conformational states
|-  
|-  


| Paper
| Paper
| [[2010Jiang2010_CTFCorrection]]
| [[2016Sorzano_Strain]]
| Amplitude correction method
| Calculate local stretches, strains and rotations from two conformational states
|-  
|-  


| Paper
| Paper
| [[2010Kasantsev_CTFCorrection]]
| [[2017Punjani_CryoSPARC]]
| Mathematical foundations of Kornberg and Jensen method
| CryoSPARC
|-  
|-  


| Paper
| Paper
| [[2010Leong_CTFCorrection]]
| [[2017Schillbach_Warpcraft]]
| Correction for spatially variant CTF
| Warpcraft: 3D Reconstruction in the presence of continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2011Glaeser_Coma]]
| [[2018Anden_Covariance]]
| The effect of coma at high-resolution
| Structural Variability from Noisy Tomographic Projections
|-  
|-  


| Paper
| Paper
| [[2011Mariani_Tilted]]
| [[2018Haselbach_FreeEnergy]]
| CTF simulation and correction of tilted specimens
| Analysis of the free energy landscape through PCA
|-  
|-  


| Paper
| Paper
| [[2011Sindelar_Wiener]]
| [[2018Nakane_MultiBody]]
| CTF correction using a modified version of Wiener filter
| Structural Variability through multi-body refinement
|-  
|-  


| Paper
| Paper
| [[2011Voortman_Tilted]]
| [[2019Serna_Review]]
| CTF correction for tilted specimen
| Review of classification tools
|-  
|-  


| Paper
| Paper
| [[2012Voortman_VaryingCTF]]
| [[2018Solernou_FFEA]]
| Correcting a spatially varying CTF
| Fluctuating Finite Element Analysis, continuum approach to Molecular Dynamics
|-  
|-  


| Paper
| Paper
| [[2013Vargas_FastDef]]
| [[2019Sorzano_Review]]
| Fast defocus
| Review of continuous heterogeneity biophysics
|-  
|-  


| Paper
| Paper
| [[2014Penczek_CTER]]
| [[2019Zhang_Local]]
| Estimation of the CTF errors
| Local variability and covariance
|-  
|-  


| Paper
| Paper
| [[2015Rohou_CTFFind4]]
| [[2020Dashti_Landscape]]
| CTF Find 4
| Retrieving functional pathways from single particle snapshots
|-  
|-  


| Paper
| Conference
| [[2015Sheth_CTFquality]]
| [[2020Gupta_MultiCryoGAN]]
| Visualization and quality assessment of CTF
| Reconstruction of continuously heterogeneous structures with adversarial networks
|-  
|-  


| Paper
| Paper
| [[2016Zhang_GCTF]]
| [[2020Harastani_NMA]]
| gCTF
| HEMNMA in Scipion : Using HEMNMA for analyzing continuous heterogeneity with normal modes
|-  
|-  


| Paper
| Paper
| [[2018Su_GoCTF]]
| [[2020Maji_Propagation]]
| goCTF, CTF for tilted specimens
| Propagation of conformational coordinates across angular space
|-  
|-  


| Paper
| Paper
| [[2020Heimowitz_Aspire]]
| [[2020Moscovich_DiffusionMaps]]
| CTF determination in Aspire
| Heterogeneity analysis by diffusion maps and spectral volumes
|-  
|-  


| Paper
| Paper
| [[2020Zivanov_HighOrder]]
| [[2020Seitz_Polaris]]
| Estimation of high order aberrations
| Analysis of energy landscapes to find minimal action paths
|-  
|-  


|}
| Conference
| [[2020Zhong_CryoDRGN]]
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
|-


=== Segmentation ===
| Paper
 
| [[2020Verbeke_Separation]]
{|
| Heterogeneity analysis by comparing common lines
|-


| Paper
| Paper
| [[2006Baker_segmentation]]
| [[2021Chen_GM]]
| Segmentation of molecular subunits
| Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability
|-  
|-  


| Paper
| Paper
| [[2010Pintilie_segger]]
| [[2021Giraldo_cryoBIFE]]
| Segmentation of molecular subunits
| A Bayesian approach to extracting free‑energy profiles
|-  
|-  


| Conference
| Conference
| [[2017Nissenson_VolumeCut]]
| [[2021Hamitouche_NMADL]]
| Segmentation of an EM volume using an atomic model
| Continuous heterogeneity analysis through normal modes and deep learning
|-  
|-  


| Paper
| Paper
| [[2019Beckers_FDR]]
| [[2021Herreros_Zernikes3D]]
| Segmentation of the protein using False Discovery Rate
| Continuous heterogeneity analysis through Zernikes 3D
|-  
|-  


| Paper
| Paper
| [[2020Beckers_FDR]]
| [[2021Kazemi_Enrich]]
| Segmentation of the protein using False Discovery Rate (GUI)
| ENRICH: A fast method to improve the quality of flexible macromolecular reconstructions
|-  
|-  


| Paper
| Paper
| [[2020Farkas_MemBlob]]
| [[2021Matsumoto_DEFmap]]
| Segmentation of membrane in membrane embedded proteins
| Prediction of RMSF of Molecular Dynamics from a CryoEM map using deep learning
|-  
|-  


| Paper
| Chapter
| [[2020Terashi_MainMastSeg]]
| [[2021Nakasako_Landscape]]
| Segmentation of proteins into domains
| Estimation of free-energy landscape from images
|-  
|-  


| Paper
| Paper
| [[2021He_EMNUSS]]
| [[2021Punjani_3DVA]]
| EMNUSS: Identification of secondary structure in CryoEM maps with deep learning
| 3D Variability analysis from images
|-  
|-  
|}
=== Fitting and docking ===
{|


| Paper
| Paper
| [[1999Volkmann_Fitting]]
| [[2021Sorzano_PCA]]
| Fitting in real space
| PCA is limited to low-resolution
|-  
|-  


| Paper
| Paper
| [[2001Baker_Review]]
| [[2021Zhong_CryoDRGN]]
| Review of protein structure prediction
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
|-  
|-  


| Paper
| Paper
| [[2001Jones_Review]]
| [[2022Arnold_liganded]]
| Review of protein structure prediction
| Test to see if liganded states can be detected
|-  
|-  


| Paper
| Paper
| [[2003Kovacs_FRM3D]]
| [[2022Ecoffet_MorphOT]]
| Fast Rotational Alignment of two EM maps
| More physically plausible morphing between two states
|-  
|-  


| Paper
| Paper
| [[2004Tama_NMA1]]
| [[2022Gomez_Hierarchical]]
| Flexible fitting with Normal Modes (I)
| Hierarchical classification of particles
|-  
|-  


| Paper
| Paper
| [[2004Tama_NMA2]]
| [[2022Hamitouche_DeepHEMNMA]]
| Flexible fitting with Normal Modes (II)
| DeepHEMNMA: Continuous heterogeneity analysis through normal modes and deep learning
|-  
|-  


| Paper
| Conference
| [[2005Velazquez_Superfamilies]]
| [[2022Levy_CryoFire]]
| Recognition of the superfamily folding in medium-high resolution volumes
| CryoFire: heterogeneity and alignment through amortized inference
|-  
|-  


| Paper
| Paper
| [[2007DeVries_Haddock]]
| [[2022Rabuck_Quant]]
| Docking with Haddock 2.0
| Workflow for discrete heterogeneity analysis
|-  
|-  


| Paper
| Paper
| [[2007Kleywegt_QualityControl]]
| [[2022Seitz_ESPER]]
| Quality control and validation of fitting
| ESPER through manifold embeddings
|-  
|-  


| Paper
| Paper
| [[2008Rusu_Interpolation]]
| [[2022Skalidis_Endogenous]]
| Biomolecular pleiomorphism probed by spatial interpolation of coarse models
| AI tools to recognize proteins in cellular fractions
|-  
|-  


| Paper
| Paper
| [[2012Biswas_Secondary]]
| [[2022Wu_Manifold]]
| Secondary structure determination in EM volumes
| Continuous heterogeneity through manifold learning
|-  
|-  


| Paper
| Paper
| [[2012Velazquez_Constraints]]
| [[2022Zhou_Data]]
| Multicomponent fitting by using constraints from other information sources
| Determination of the number of discrete 3D classes
|-  
|-  


| Paper
| Paper
| [[2013Chapman MS_Atomicmodeling]]
| [[2023Barchet_Focused]]
| Atomic modeling of cryo-electron microscopy reconstructions--joint refinement of model and imaging parameters
| Applications and strategies in focused classification and refinement
|-  
|-  


| Paper
| Paper
| [[2013Esquivel_Modelling]]
| [[2023Afonine_Varref]]
| Review on modelling (secondary structure, fitting, ...)
| Phenix.varref for the analysis of the model heterogeneity
|-  
|-  


| Paper
| Paper
| [[2013Lopez_Imodfit]]
| [[2023Chen_GMM]]
| Fitting based on vibrational analysis
| Continuous heterogeneity analysis with GMMs and neural networks
|-  
|-  


| Paper
| Paper
| [[2013Nogales_3DEMLoupe]]
| [[2023Dsouza_benchmark]]
| Normal Mode Analysis of reconstructed volumes
| Benchmark analysis of various continuous heterogeneity algorithms
|-  
|-  


| Paper
| Paper
| [[2014AlNasr_Secondary]]
| [[2023Esteve_Spectral]]
| Identification of secondary structure elements in EM volumes
| Continuous heterogeneity analysis through the spectral decomposition of the atomic structure
|-  
|-  


| Paper
| Paper
| [[2014Politis_MassSpect]]
| [[2023Fernandez_Subtraction]]
| Integration of mass spectroscopy information
| Subtraction of unwanted signals to improve classification and alignment
|-  
|-  


| Paper
| Paper
| [[2014Rey_MassSpect]]
| [[2023Forsberg_Filter]]
| Integration of mass spectroscopy information
| Filter to estimate the local heterogeneity
|-  
|-  


| Paper
| Paper
| [[2014Villa_Review]]
| [[2023Herreros_Hub]]
| Review of atomic fitting into EM volumes
| Flexibility hub: an integrative platform for continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2015Barad_EMRinger]]
| [[2023Luo_OpusDSD]]
| Validation of hybrid models
| OPUS DSD: a neural network approach to continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2015Bettadapura_PF2Fit]]
| [[2023Kinman_Analysis]]
| Fast rigid fitting of PDBs into EM maps
| Analysis of the continuous heterogeneity results of CryoDrgn
|-  
|-  


| Paper
| Paper
| [[2015Carrillo_CapsidMaps]]
| [[2023Matsumoto_DEFmap]]
| Analysis of virus capsids using Google Maps
| Quantitative analysis of the prediction of RMSF from a map using DefMap
|-  
|-  


| Paper
| Paper
| [[2015Hanson_Continuum]]
| [[2023Punjani_3DFlex]]
| Modelling assemblies with continuum mechanics
| Continuous heterogeneity through 3DFlex
|-  
|-  


| Paper
| Paper
| [[2015Lopez_Review]]
| [[2023Seitz_Geometric]]
| Review of structural modelling from EM data
| Geometric relationships between manifold embeddings of a continuum of 3D molecular structures and their 2D projections
|-  
|-  


| Paper
| Paper
| [[2015Schroeder_Hybrid]]
| [[2023Seitz_ESPER]]
| Review on model building
| Continuous heterogeneity through Embedded subspace partitioning and eigenfunction realignment
|-  
|-  


| Paper
| Paper
| [[2015Tamo_Dynamics]]
| [[2023Tang_Reweighting]]
| Dynamics in integrative modeling
| Ensemble reweighting using Cryo-EM particles
|-  
|-  


| Paper
| Paper
| [[2015Sorzano_AtomsToVoxels]]
| [[2023Vuillemot_MDSPACE]]
| Accurate conversion of an atomic model into a voxel density volume
| MDSPACE: Continuous heterogeneity analysis through normal modes and MD simulation
|-  
|-  


| Paper
| Paper
| [[2016Joseph_Evolution]]
| [[2023Wang_Autoencoder]]
| Evolutionary constraints for the fitting of atomic models into density maps
| Discrete heterogeneity based on autoencoders
|-  
|-  


| Paper
| Paper
| [[2016Joseph_Refinement]]
| [[2024Amisaki_Multilevel]]
| Refinement of atomic models in high-resolution EM reconstructions using Flex-EM
| Multilevel PCA for the analysis of hierarchical continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2016Murshudov_Refinement]]
| [[2024Chen_Focused]]
| Refinement of atomic models in high-resolution EM reconstructions
| Focused reconstruction of heterogeneous macromolecules
|-  
|-  


| Paper
| Paper
| [[2016Segura_3Diana]]
| [[2024Fan_CryoTrans]]
| Validation of hybrid models
| CryoTrans: Trajectory generation between two states
|-  
|-  


| Paper
| Paper
| [[2016Singharoy_MDFF]]
| [[2024Klindt_Disentanglement]]
| Construction of hybrid models driven by EM density and molecular dynamics
| Disentanglement of pose and conformation in the latent space of heterogeneity analysis algorithms
|-
 
| Conference
| [[2024Levy_Hydra]]
| Hydra: Continuous and discrete heterogeneity using neural fields
|-  
|-  


| Paper
| Paper
| [[2016Wang_Rosetta]]
| [[2024Li_CryoStar]]
| Construction of hybrid models driven by EM density using Rosetta
| CryoStar: Continuous heterogeneity analysis with structural priors
|-  
|-  


| Paper
| Paper
| [[2017Chen_CoarseGraining]]
| [[2024Schwab_DynaMight]]
| Coarse graining of EM volumes
| DynaMight: Heterogeneity analysis using neural networks
|-  
|-  


| Paper
| Paper
| [[2017Joseph_Metrics]]
| [[2024Shi_Priors]]
| Metrics analysis for the comparison of structures
| Latent space priors for continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2017Hryc_WeightedAtoms]]
| [[2024Song_RMSFNet]]
| Construction of hybrid models by locally weighting the different atoms
| RMSFNet: prediction of Molecular Dynamics RMSF from the cryoEM map
|-  
|-  


| Paper
| Paper
| [[2017Matsumoto_Distribution]]
| [[2024Yoshidome_4D]]
| Estimating the distribution of conformations of atomic models
| Heterogeneity analysis using molecular dynamics
|-  
|-  


| Paper
| Paper
| [[2017Michel_ContactPrediction]]
| [[2025Chen_GMM]]
| Structure prediction by contact prediction
| Continuous heterogeneity analysis in SPA using atomic models
|-  
|-  


| Paper
| Paper
| [[2017Miyashita_EnsembleFitting]]
| [[2025Dingeldein]]
| Ensemble fitting using Molecular Dynamics
| Amortized template matching using simulation-based inference
|-  
|-  


| Paper
| Paper
| [[2017Turk_ModelBuilding]]
| [[2025Herreros_HetSiren]]
| Tutorial on model building and protein visualization
| Discrete and Continuous heterogeneity analysis using neural networks
|-  
|-  


| Paper
| Paper
| [[2017Wang_PartialCharges]]
| [[2025Gilles_Covariance]]
| Appearance of partial charges in EM maps
| Continuous heterogeneity analysis using regularized covariance estimation and kernel regression
|-  
|-  


| Paper
| Paper
| [[2017Wlodawer]]
| [[2025Kinman_SIREN]]
| Comparison of X-ray and EM high resolution structures
| Heterogeneity analysis using coocurrence analysis (SIREN)
|-  
|-  


| Paper
| Paper
| [[2018Cassidy_review]]
| [[2025Lauzirika_Distinguishable]]
| Review of methods for hybrid modeling
| How many (distinguishable) classes can we identify in single-particle analysis?
|-  
|-  


| Paper
| Paper
| [[2018Chen_SudeChains]]
| [[2025Levy_CryoDRGNAI]]
| A comparison of side chains between X-ray and EM maps
| CryoDRGN-AI: Heterogeneity analysis and ab initio 3D reconstruction for SPA and STA
|-  
|-  
|}
=== Validation ===
{|


| Paper
| Paper
| [[2018Kawabata_Pseudoatoms]]
| [[2008Stagg_TestBed]]
| Modelling the EM map with Gaussian pseudoatoms
| Effect of voltage, dosis, number of particles and Euler jumps on resolution
|-  
|-  


| Paper
| Paper
| [[2018Kovacs_Medium]]
| [[2011Henderson]]
| Modelling of medium resolution EM maps
| Tilt Validation
|-  
|-  


| Paper
| Paper
| [[2018Neumann_validation]]
| [[2011Read]]
| Validation of fitting, resolution assessment and quality of fit
| Validation of PDBs
|-  
|-  


| Paper
| Paper
| [[2018Terwilliger_map_to_model]]
| [[2012Henderson]]
| Phenix map_to_model, automatic modelling of EM volumes
| EM Map Validation
|-  
|-  


| Paper
| Paper
| [[2018Wang_MD]]
| [[2013Cossio_Bayesian]]
| Constructing atomic models using molecular dynamics
| EM Map Validation in a probabilistic setting
|-  
|-  


| Paper
| Paper
| [[2018Xia_MVPENM]]
| [[2013Chen_NoiseSubstitution]]
| Multiscale Normal Mode Analysis
| Noise substitution at high resolution for measuring overfitting
|-  
|-  


| Paper
| Paper
| [[2018Yu_Atomic]]
| [[2013Ludtke_Validation]]
| Constructing atomic models using existing tools
| Structural validation, example of the Calcium release channel
|-  
|-  


| Paper
| Paper
| [[2019Bonomi_Multiscale]]
| [[2013Murray_Validation]]
| Bayesian multi-scale modelling
| Validation of a 3DEM structure through a particular example
|-  
|-  


| Paper
| Paper
| [[2019Kidmose_Namdinator]]
| [[2014Russo_StatisticalSignificance]]
| Namdinator: Flexible fitting with NAMD
| EM Map Validation through the statistical significance of the tilt-pair angular assignment
|-  
|-  


| Paper
| Paper
| [[2019Klaholz_Review]]
| [[2014Stagg_Reslog]]
| Review of Phenix tools to modelling
| EM Map Validation through the resolution evolution with the number of particles
|-  
|-  


| Paper
| Paper
| [[2019Subramaniya_DeepSSE]]
| [[2014Wasilewski_Tilt]]
| Secondary structure prediction from maps using deep learning
| Web implementation of the tilt pair validation
|-  
|-  


| Paper
| Paper
| [[2019Zhang_CoarseGrained]]
| [[2015Heymann_Alignability]]
| Coarse-graining of EM maps
| EM Map Validation through the resolution of reconstructions from particles and noise
|-  
|-  


| Paper
| Paper
| [[2020Costa_MDeNM]]
| [[2015Oliveira_FreqLimited]]
| Flexible fitting with molecular dynamics and normal modes
| Comparison of gold standard and frequency limited optimization
|-  
|-  


| Paper
| Paper
| [[2020Cragnolini_Tempy2]]
| [[2015Rosenthal_Review]]
| TEMpy2 library for density-fitting and validation
| Review of validation methods
|-  
|-  


| Paper
| Paper
| [[2020Dodd_ModelBuilding]]
| [[2015Wriggers_Secondary]]
| Model building possibilities, with special emphasis on flexible fitting
| Validation by secondary structure
|-  
|-  


| Paper
| Paper
| [[2020Ho_CryoID]]
| [[2016Degiacomi_IM]]
| Identification of proteins in structural proteomics from cryoEM volumes
| Comparison of Ion Mobility data and EM volumes
|-  
|-  


| Paper
| Paper
| [[2020Hoh_Buccaneer]]
| [[2016Kim_SAXS]]
| Structure modelling with Buccaneer
| Comparison of SAXS data and EM projections
|-  
|-  


| Paper
| Paper
| [[2020Joseph_comparison]]
| [[2016Rosenthal_Review]]
| Comparison of map and model, or two maps
| Review of validation methods
|-  
|-  


| Paper
| Paper
| [[2020Kim_Review]]
| [[2016Vargas_Alignability]]
| Review of the options for atomic modelling
| Validation by studying the tendency of an angular assignment to cluster in the projection space
|-  
|-  


| Paper
| Paper
| [[2020Leelananda_Constraints]]
| [[2017Monroe_PDBRefinement]]
| NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD structure refinement
| Validation by comparison to a refined PDB
|-  
|-  


| Paper
| Paper
| [[2020Liebschner_Ceres]]
| [[2018Afonine_Phenix]]
| CERES: Web server of refined atomic maps of CryoEM deposited maps by Phenix
| Tools in Phenix for the validation of EM maps
|-  
|-  


| Paper
| Paper
| [[2020Oroguchi]]
| [[2018Heymann_Bsoft]]
| Assessment of Force Field Accuracy Using Cryogenic Electron Microscopy Data
| Map validation using Bsoft
|-  
|-  


| Paper
| Paper
| [[2020Vant_Flexible]]
| [[2018Heymann_Challenge]]
| Flexible fitting with molecular dynamics and neural network potentials
| A summary of the assessments of the 3D Map Challenge
|-  
|-  


| Paper
| Paper
| [[2021Behkamal_Secondary]]
| [[2018Jonic_Gaussian]]
| Secondary structure from medium resolution maps
| Assessment of sets of volumes by pseudoatomic structures
|-  
|-  


| Paper
| Paper
| [[2021Chojnowski_quality]]
| [[2018Naydenova_AngularDistribution]]
| Quality of models automatically fitted with ARP/wARP
| Evaluating the angular distribution of a 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2021Han_Vesper]]
| [[2018Pages_Symmetry]]
| VESPER: global and local cryo-EM map alignment using local density vectors
| Looking for a symmetry axis in a PDB
|-  
|-  


| Paper
| Paper
| [[2021Lawson_Challenge]]
| [[2018Pintilie_SSE]]
| Validation recommendations based on outcomes of the 2019 EMDataResource challenge
| Evaluating the quality of SSE and side chains
|-  
|-  


| Paper
| Paper
| [[2021Mori_Flexible]]
| [[2019Herzik_Multimodel]]
| Efficient Flexible Fitting Refinement with Automatic Error Fixing
| Local and global quality by multi-model fitting
|-  
|-  


| Paper
| Paper
| [[2021Pfab_DeepTracer]]
| [[2020Chen_Atomic]]
| DeepTracer for fast de novo cryo-EM protein structure modeling
| Validation of the atomic models derived from CryoEM
|-  
|-  


| Paper
| Paper
| [[2021Saltzberg_IMP]]
| [[2020Cossio_CrossValidation]]
| Using the Integrative Modeling Platform to model a cryoEM map
| Need for cross validation
|-  
|-  


| Paper
| Paper
| [[2021Terwilliger_CryoID]]
| [[2020Ortiz_CrossValidation]]
| Identification of sequence in a CryoEM map from a set of candidates
| Cross validation for SPA
|-  
|-  


| Paper
| Paper
| [[2021Titarenko_LocalCorr]]
| [[2020Sazzed_helices]]
| Performance improvement of local correlation for docking
| Validation of helix quality
|-  
|-  


| Conference
| Paper
| [[2021Vuillemot_NMA]]
| [[2020Stojkovic_PTM]]
| Flexible fitting using Normal Modes
| Validation of post-translational modifications
|-  
|-  


| Paper
| Paper
| [[2022Antanasijevic_ab]]
| [[2020Tiwari_PixelSize]]
| Sequence determination of antibodies bound to a map
| Fine determination of the pixel size
|-  
|-  


| Paper
| Paper
| [[2022Chojnowski_findMySeq]]
| [[2021Mendez_Graph]]
| Identify sequence in CryoEM map using Deep Learning
| Identification of incorrectly oriented particles
|-  
|-  


| Paper
| Paper
| [[2022Vuillemot_NMMD]]
| [[2021Pintilie_Validation]]
| Flexible fitting with simultaneous Normal Mode and Molecular Dynamics displacements
| Review of map validation approaches
|-  
|-  


| Paper
| Paper
| [[2022Zhang_CRITASSER]]
| [[2021Olek_FDR]]
| Atomic models of assemble protein structures with deep learning
| Cryo-EM Map–Based Model Validation Using the False Discovery Rate Approach
|-  
|-  


|}
| Paper
| [[2022Garcia_DeepHand]]
| Checking the correct handedness with a neural network
|-


=== Books and reviews ===
| Paper
| [[2022Sorzano_Bias]]
| Bias, variance, gold-standard and overfitting in SPA
|-


{|
| Paper
| [[2022Sorzano_Validation]]
| Validation scheme and server for SPA
|-


| Book
| Paper
| [[1980Herman_Tomography]]
| [[2022Terashi_DAQ]]
| General book on tomography
| Validation of models fitted into CryoEM maps
|-  
|-  


| Book
| Paper
| [[1988Kak_Tomography]]
| [[2022Waarshamanage_EMDA]]
| General book on tomography
| Validation of models fitted into CryoEM maps
|-  
|-  


| Paper
| Paper
| [[2000Tao_Review]]
| [[2024Feng_DeepQs]]
| Review of single particles
| DeepQ: Local quality of the map
|-  
|-  


| Paper
| Paper
| [[2000VanHeel_Review]]
| [[2024Jeon_CryoBench]]
| Review of single particles
| Datasets for heterogeneity benchmarking
|-  
|-  


| Paper
| Paper
| [[2002Frank_Review]]
| [[2024Lytje_SAXS]]
| Review of single particles
| Validation of CryoEM maps with SAXS curves
|-  
|-  


| Paper
| Paper
| [[2002Schmid_Review]]
| [[2024Sanchez_Anisotropy]]
| Review of single particles
| New measure of anisotropy in maps
|-  
|-  


| Paper
| Paper
| [[2004Henderson_Review]]
| [[2024Verbeke_SelfFSC]]
| Review of electron microscopy
| Self FSC: FSC with a single map
|-  
|-  


| Paper
| Paper
| [[2004Subramaniam_Review]]
| [[2025Bromberg_Hand]]
| Review of single particles
| Handedness validation based on the Ewald sphere
|-  
|-  


| Paper
| Paper
| [[2005Steven_Review]]
| [[2025Pintilie_QScore]]
| Review of electron microscopy
| Extension of Q-Score to analyze SPA maps
|-  
|-  
|}
=== Resolution ===
{|


| Paper
| Paper
| [[2006Fernandez_Review]]
| [[1986Harauz_FBP]]
| Review of electron microscopy
| Fourier Shell Correlation
|-
 
| Book
| [[2006Frank_book]]
| Book covering all aspects of electron microscopy of single particles
|-  
|-  


| Paper
| Paper
| [[2006Sorzano_Review]]
| [[1987Unser_SSNR]]
| Review of optimization problems in electron microscopy
| 2D Spectral Signal to Noise Ratio
|-  
|-  


| Paper
| Paper
| [[2007Leschziner_Review]]
| [[2002Penczek_SSNR]]
| Review of 3D heterogeneity handling algorithms
| 3D Spectral Signal to Noise Ratio for Fourier based algorithms
|-  
|-  


| Paper
| Paper
| [[2007Sorzano_Review]]
| [[2003Rosenthal_DPR]]
| Review of the image processing steps
| Review of the FSC and establishment of a new threshold
|-  
|-  


| Paper
| Paper
| [[2008Fanelli_ImageFormation]]
| [[2005Unser_SSNR]]
| Review on the image formation model from the electron waves and open inverse-problems in Electron Tomography
| 3D Spectral Signal to Noise Ratio for any kind of algorithms
|-  
|-  


| Paper
| Paper
| [[2008Fernandez_HPCReview]]
| [[2005VanHeel_FSC]]
| High performance computing in electron cryomicroscopy
| Establishment of a new threshold for FSC
|-  
|-  


| Paper
| Paper
| [[2008Jonic_Review]]
| [[2007Sousa_AbInitio]]
| Comparison between electron tomography and single particles
| Resolution measurement on neighbour Fourier voxels
|-  
|-  


| Paper
| Paper
| [[2008Mueller_Review]]
| [[2014Kucukelbir_Local]]
| Review of Electron microscopy
| Quantifying the local resolution of cryo-EM density maps
|-  
|-  


| Paper
| Paper
| [[2008Taylor_Review]]
| [[2016Pintilie_Probabilistic]]
| Review of Electron microscopy
| Probabilistic models and resolution
|-  
|-  


| Paper
| Paper
| [[2010DeRosier_Review]]
| [[2017Sorzano_FourierProperties]]
| Personal account of how 3DEM developed in the early days
| Statistical properties of resolution measures defined in Fourier space
|-  
|-  


| Chapter
| Conference
| [[2012Sorzano_Review]]
| [[2018Avramov_DeepLearning]]
| Review of single particle analysis using Xmipp
| Deep learning classification of volumes into low, medium and high resolution
|-  
|-  


| Chapter
| Paper
| [[2012Devaux_Protocol]]
| [[2018Carugo_BFactors]]
| Protocols for performing single particle analysis
| How large can B-factors be in protein crystals
|-  
|-  


| Paper
| Conference
| [[2014Bai_Review]]
| [[2018Kim_FourierError]]
| Recent advances in cryo-EM
| Comparison between a gold standard and a reconstruction
|-  
|-  


| Paper
| Paper
| [[2015Carazo_Review]]
| [[2018Rupp_Problems]]
| Review of the reconstruction process
| Problems of resolution as a proxy number for map quality
|-  
|-  


| Paper
| Paper
| [[2015Cheng_Review]]
| [[2018Vilas_MonoRes]]
| A primer to Single Particle Cryo-EM
| Local resolution by monogenic signals
|-  
|-  


| Paper
| Paper
| [[2015Cheng_Reviewb]]
| [[2018Yang_Multiscale]]
| Single Particle Cryo-EM at crystallographic resolution
| Resolution from a multiscale spectral analysis
|-  
|-  


| Paper
| Paper
| [[2015Elmlund_Review]]
| [[2019Avramov_DeepLearning]]
| Recent advances in cryo-EM
| Deep learning classification of volumes into low, medium and high resolution
|-  
|-  


| Paper
| Paper
| [[2015Henderson_Review]]
| [[2019Heymann_Statistics]]
| Recent advances in cryo-EM
| SNR, FSC, and related statistics
|-  
|-  


| Paper
| Paper
| [[2015Nogales_Review]]
| [[2019Ramirez_DeepRes]]
| Recent advances in cryo-EM
| Resolution determination by deep learning
|-  
|-  


| Paper
| Paper
| [[2015Schroeder_Review]]
| [[2020Baldwin_Lyumkis_SCF]]
| Review of advances in the electron microscope
| Resolution attenuation through non-uniform Fourier sampling
|-  
|-  


| Paper
| Paper
| [[2015VanDenBedem_Integrative]]
| [[2020Beckers_Permutation]]
| Review of integrative structural biology
| Permutation tests for the FSC
|-  
|-  


| Paper
| Paper
| [[2015Wu_Review]]
| [[2020Penczek_mFSC]]
| Review of advances in cryo-EM
| Modified FSC to avoid mask induced artifacts
|-  
|-  


| Paper
| Paper
| [[2016Carroni_CryoEM]]
| [[2020Vilas_MonoDir]]
| Review of advances in Cryo-EM
| Local and directional resolution
|-  
|-  


| Paper
| Paper
| [[2016Egelman_CryoEM]]
| [[2023Dai_CryoRes]]
| Review of advances in Cryo-EM
| Local resolution through deep learning
|-  
|-  


| Paper
| Paper
| [[2016Eisenstein_CryoEM]]
| [[2023Vilas_FSO]]
| News feature on the Method of the Year
| Fourier Shell Occupancy to measure anisotropy
|-  
|-  


| Paper
| Paper
| [[2016FernandezLeiro_Review]]
| [[2025Urzhumtsev_RescaleFSC]]
| Review of EM
| Rescaling of the FSC
|-  
|-  


|}
=== Sharpening of high resolution information ===
{|
| Paper
| Paper
| [[2016Glaeser_HowGood]]
| [[2003Rosenthal_DPR]]
| How good can cryo-EM become?
| Contrast restoration and map sharpening
|-  
|-  


| Paper
| Paper
| [[2016Jonic_PseudoAtoms]]
| [[2008Fernandez_Bfactor]]
| Review of the applications of the use of pseudoatoms in EM
| Bfactor determination and restoration
|-
 
| Chapter
| [[2016Mio_Review]]
| Overview of the process to obtain EM reconstructions
|-  
|-  


| Paper
| Paper
| [[2016Jonic_Review]]
| [[2013Fiddy_SaxtonAlgorithm]]
| A review of computational ways to handle heterogeneity
| Phase retrieval or extension
|-  
|-  


| Paper
| Paper
| [[2016Nogales_Review]]
| [[2014Kishchenko_SphericalDeconvolution]]
| Review of advances in cryo-EM
| Spherical deconvolution
|-  
|-  


| Paper
| Paper
| [[2016Subramaniam_Review]]
| [[2015Spiegel_VISDEM]]
| Why cryo-EM is now suitable for crystallographic journals
| Visualization improvement by the use of pseudoatomic profiles
|-  
|-  


| Paper
| Paper
| [[2016Vinothkumar_Review]]
| [[2016Jonic_Pseudoatoms]]
| Historical review and current limitations
| Approximation with pseudoatoms
|-  
|-  


| Report
| Paper
| [[2017Brezinski_Nobel]]
| [[2016Jonic_Denoising]]
| Scientific background on the Nobel Prize in Chemistry 2017
| Denoising and high-frequency boosting by pseudoatom approximation
|-  
|-  


| Paper
| Paper
| [[2017Cheng_review]]
| [[2017Jakobi_LocScale]]
| Why CryoEM became so hot
| Sharpening based on an atomic model
|-  
|-  


| Paper
| Paper
| [[2017Danev_Review]]
| [[2019Ramlaul_Filtering]]
| Review of the use of phase plates in EM
| Local agreement filtering (denoising)
|-  
|-  


| Paper
| Conference
| [[2017Elmlund_Review]]
| [[2020Mullick_SuperResolution]]
| Review of the main current difficulties of EM
| Superresolution from a map
|-  
|-  


| Paper
| Paper
| [[2017Frank_Review]]
| [[2020Ramirez_LocalDeblur]]
| Historical review of EM
| Local deblur (local Wiener filter)
|-  
|-  


| Paper
| Paper
| [[2017Frank_TimeResolved]]
| [[2020Terwilliger_density]]
| Review of time-resolved of EM
| Density modification of CryoEM maps
|-  
|-  


| Paper
| Paper
| [[2017Jonic_Review]]
| [[2020Vilas_Bfactor]]
| Review of computational methods to analyze conformational variability
| Global B-factor correction does not represent macromolecules
|-  
|-  


| Paper
| Paper
| [[2017Merino_DrugEM]]
| [[2021Beckers_Interpretation]]
| Applications of EM for drug design
| Improvements from the raw reconstruction to a structure to model
|-  
|-  


| Paper
| Paper
| [[2017Rawson_Limitations]]
| [[2021Kaur_LocSpiral]]
| Limitations of EM for drug design
| LocSpiral, LocBsharpen, LocBfactor
|-  
|-  


| Paper
| Paper
| [[2017Sorzano_FourierProperties]]
| [[2021Fernandez_Adjustment]]
| Review of statistical properties of resolution measures defined in Fourier space
| Map adjustment for subtraction, consensus and sharpening
|-  
|-  


| Paper
| Paper
| [[2017Sorzano_SurveyIterative]]
| [[2021Sanchez_DeepEMhancer]]
| Survey of iterative reconstruction methods for EM
| Deep learning algorithm for volume restoration
|-  
|-  


| Paper
| Paper
| [[2018Bruggeman_Crowdsourcing]]
| [[2022Gilles_Wilson]]
| Exploring crowdsourcing for EM image processing
| A molecular prior distribution for Bayesian inference based on Wilson statistics
|-  
|-  


| Paper
| Paper
| [[2018Cheng_Review]]
| [[2022Vargas_tubular]]
| Review of EM and future ahead
| Map enhancement by multiscale tubular filter
|-  
|-  


| Paper
| Paper
| [[2018Cossio_ML]]
| [[2023He_EMReady]]
| Review of Maximum Likelihood methods
| Map enhancement with local and non-local deep learning (EMReady)
|-  
|-  


| Paper
| Paper
| [[2018Grimes_Crystallography]]
| [[2023Maddhuri_EMGan]]
| Review of X-ray crystallography and its relationship to EM
| Map enhancement with GANs (EMGan)
|-  
|-  


| Paper
| Paper
| [[2018Murata_Review]]
| [[2024Agarwal_crefDenoiser]]
| Review of EM for structure dynamics
| cRefDenoiser: map denoising based on deep learning
|-  
|-  


| Paper
| Paper
| [[2018Quentin_Biomedical]]
| [[2024Kimanius_Blush]]
| Review of EM as a tool for biomedical research
| Blush: data-driven regularization
|-  
|-  


| Paper
| Paper
| [[2018Scapin_DrugDiscovery]]
| [[2025Selvaraj_CryoTEN]]
| Review of EM as a tool for drug discovery
| CryoTEN: map enhancement using transformers
|-  
|-  


| Paper
|}
| [[2018Vilas_ImageProcessing]]
 
| Review of the recent developments in image processing for single particle analysis
=== CTF estimation and restoration ===
|-
 
{|


| Paper
| Paper
| [[2018vonLoeffelholz_VPP]]
| [[1982Schiske_Correction]]
| Comparison of Volta Phase Plate reconstructions close to focus and with defocus
| CTF correction for tilted objects
|-  
|-  


| Paper
| Paper
| [[2018Eisenstein_DrugDesigners]]
| [[1988Toyoshima_Model]]
| Drug designers embrace cryo-EM
| CTF estimation
|-  
|-  


| Paper
| Paper
| [[2019Benjin_Review]]
| [[1995Frank_Wiener]]
| Review of SPA
| CTF correction using Wiener filter
|-  
|-  


| Paper
| Paper
| [[2019Danev_Review]]
| [[1996Skoglund_MaxEnt]]
| Review of future directions
| CTF correction with Maximum Entropy
|-  
|-  


| Paper
| Paper
| [[2019Lyumkis_Review]]
| [[1996Zhou_Model]]
| Challenges and reviews
| CTF model and user interface for manual fitting
|-  
|-  


| Paper
| Paper
| [[2019Sorzano_Review]]
| [[1997Fernandez_AR]]
| Review of continuous heterogeneity biophysics
| PSD estimation using periodogram averaging and AR models
|-  
|-  


| Paper
| Paper
| [[2020Abriata_Review]]
| [[1997Penczek_Wiener]]
| Considerations of structure prediction and CryoEM
| CTF correction using Wiener filter
|-  
|-  


| Paper
| Paper
| [[2020Akbar_Review]]
| [[1997Stark_Deconvolution]]
| Review of membrane protein reconstructions
| CTF correction using deconvolution
|-  
|-  


| Paper
| Paper
| [[2020Bendory_Review]]
| [[1997Zhu_RecCTF]]
| Review of image processing problems
| CTF correction and reconstruction
|-  
|-  


| Paper
| Paper
| [[2020Dubach_Review]]
| [[2000DeRosier_EwaldCorrection]]
| Review of resolution in X-ray crystallography and CryoEM
| CTF correction considering the Ewald sphere
|-  
|-  


| TechReport
| Paper
| [[2020Lai_Statistics]]
| [[2000Jensen_TiltedCorrection]]
| Review of statistical properties of image alignment
| CTF correction considering tilt in backprojection
|-  
|-  


| Paper
| Paper
| [[2020Hu_Quaternions]]
| [[2001Saad_CTFEstimate]]
| Review of the use of quaternions to describe rotations
| CTF estimation
|-  
|-  


| Paper
| Paper
| [[2020McCafferty_Review]]
| [[2003Huang_CTFEstimate]]
| Review of SPA and Mass Spectroscopy
| CTF estimation
|-  
|-  


| Paper
| Paper
| [[2020Seffernick_Hybrid]]
| [[2003Mindell_CTFTILT]]
| Review of hybrid (computational and experimental) methods to get protein structure
| CTF estimation for tilted micrographs
|-  
|-  


| Paper
| Paper
| [[2020Nakane_Atomic]]
| [[2003Sander_MSA]]
| Single-particle cryo-EM at atomic resolution
| CTF estimation through MSA classification of PSDs
|-  
|-  


| Paper
| Paper
| [[2020Vilas_Review]]
| [[2003Velazquez_ARMA]]
| Review of local resolution
| PSD and CTF estimation using ARMA models
|-  
|-  


| Paper
| Paper
| [[2020Wu_Review]]
| [[2004Sorzano_IDR]]
| Review of current limitations, with special emphasis on protein size
| CTF restoration and reconstruction with Iterative Data Refinement
|-
 
| Conference
| [[2004Wan_CTF]]
| Spatially variant CTF
|-  
|-  


| Paper
| Paper
| [[2020Singer_Sigworth_Review]]
| [[2004Zubelli_Chahine]]
| Review of single particle analysis
| CTF restoration and reconstruction with Chahine's multiplicative method
|-
|-  


| Paper
| Conference
| [[2021Bai_Review]]
| [[2005Dubowy_SpaceVariant]]
| Review of breakthroughs leading to atomic resolution
| CTF correction when this is space variant
|-
|-  


| Paper
| Paper
| [[2021DImprima_Review]]
| [[2005Mallick_ACE]]
| Review of sample preparation for single particle analysis
| CTF estimation
|-
|-  


| Paper
| Paper
| [[2021Lander_Review]]
| [[2006Wolf_Ewald]]
| Review of focused analysis in SPA
| CTF correction considering Ewald sphere
|-
|-  


| Paper
| Paper
| [[2021Raimondi_Review]]
| [[2007Jonic_EnhancedPSD]]
| General review of SPA
| PSD enhancement for better identification of Thon rings; Vitreous ice diffracts in Thon rings
|-
|-  


| Paper
| Paper
| [[2022Jones_Comment]]
| [[2007Philippsen_Model]]
| Comment on the impact of AlphaFold and next challenges ahead
| CTF Model for tilted specimens
|-
|-  


| Paper
| Paper
| [[2022Namba_Review]]
| [[2007Sorzano_CTF]]
| Review of the current state of SPA
| CTF estimation using enhanced PSDs
|-
|-  


| Paper
| Paper
| [[2022Ourmazd_Comment]]
| [[2009Sorzano_Sensitivity]]
| Comment on the impact of AlphaFold and next challenges ahead
| Error sensitivity of the CTF models, non-uniqueness of the CTF parameters
|-
|-  


| Paper
| Paper
| [[2022Palmer_Local]]
| [[2010Jiang2010_CTFCorrection]]
| Review of local methods in CryoEM
| Amplitude correction method
|-
|-  


| Paper
| Paper
| [[2022Subramaniam_Comment]]
| [[2010Kasantsev_CTFCorrection]]
| Comment on the impact of AlphaFold and next challenges ahead
| Mathematical foundations of Kornberg and Jensen method
|-
|-  


| Paper
| Paper
| [[2022Treder_DL]]
| [[2010Leong_CTFCorrection]]
| Review of Deep Learning applications in CryoEM
| Correction for spatially variant CTF
|-
|-  
 
|}
 
=== Software ===
 
{|


| Paper
| Paper
| [[1996Frank_Spider]]
| [[2011Glaeser_Coma]]
| Spider
| The effect of coma at high-resolution
|-  
|-  


| Paper
| Paper
| [[1996VanHeel_Imagic]]
| [[2011Mariani_Tilted]]
| Imagic
| CTF simulation and correction of tilted specimens
|-  
|-  


| Paper
| Paper
| [[1999Lutdke_Eman]]
| [[2011Sindelar_Wiener]]
| Eman
| CTF correction using a modified version of Wiener filter
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2011Voortman_Tilted]]
| Xmipp
| CTF correction for tilted specimen
|-  
|-  


| Paper
| Paper
| [[2007Baldwin_AngularTransformations]]
| [[2012Voortman_VaryingCTF]]
| The Transform Class in SPARX and EMAN2
| Correcting a spatially varying CTF
|-  
|-  


| Paper
| Paper
| [[2007Heymann_Bsoft]]
| [[2013Vargas_FastDef]]
| Bsoft
| Fast defocus
|-  
|-  


| Paper
| Paper
| [[2007Grigorieff_Frealign]]
| [[2014Penczek_CTER]]
| Frealign
| Estimation of the CTF errors
|-  
|-  


| Paper
| Paper
| [[2008Scheres_XmippProtocols]]
| [[2015Rohou_CTFFind4]]
| Xmipp Protocols
| CTF Find 4
|-  
|-  


| Paper
| Paper
| [[2008Shaikh_SpiderProtocols]]
| [[2015Sheth_CTFquality]]
| Spider Protocols
| Visualization and quality assessment of CTF
|-  
|-  


| Paper
| Paper
| [[2012Wriggers_SitusConventions]]
| [[2016Zhang_GCTF]]
| Conventions and workflows in Situs
| gCTF
|-  
|-  


| Paper
| Paper
| [[2013DeLaRosa_Xmipp30]]
| [[2018Su_GoCTF]]
| Xmipp 3.0
| goCTF, CTF for tilted specimens
|-  
|-  


| Paper
| Paper
| [[2015Cianfrocco_Cloud]]
| [[2020Heimowitz_Aspire]]
| Software execution in the cloud
| CTF determination in Aspire
|-  
|-  


| Paper
| Paper
| [[2015Cheng_MRC2014]]
| [[2020Zivanov_HighOrder]]
| Extensions to MRC file format
| Estimation of high-order aberrations
|-  
|-  


| Paper
| Paper
| [[2013DeLaRosa_Scipion]]
| [[2022Pant_ExitWave]]
| Scipion
| Estimation of the electron exit-wave
|-  
|-  


| Paper
| Paper
| [[2016Scheres_Relion]]
| [[2023Fernandez_Local]]
| Tutorial on the use of Relion
| Local defocus estimation
|-  
|-  


| Paper
| Paper
| [[2016Grigorieff_Frealign]]
| [[2025Elferich_CTFFind5]]
| Tutorial on the use of Frealign
| Quality, tilt, and thickness of TEM samples with CTFFind5
|-  
|-  
|}
=== Segmentation ===
{|


| Paper
| Paper
| [[2017Moriya_Sphire]]
| [[2006Baker_segmentation]]
| Tutorial on the use of Sphire
| Segmentation of molecular subunits
|-  
|-  


| Paper
| Paper
| [[2018Bell_EMAN2]]
| [[2010Pintilie_segger]]
| New tools in EMAN2
| Segmentation of molecular subunits
|-  
|-  


| Paper
| Conference
| [[2018Cianfrocco_cloud]]
| [[2017Nissenson_VolumeCut]]
| CryoEM Cloud Tools
| Segmentation of an EM volume using an atomic model
|-  
|-  


| Paper
| Paper
| [[2018Grant_cisTEM]]
| [[2019Beckers_FDR]]
| cisTEM
| Segmentation of the protein using False Discovery Rate
|-  
|-  


| Paper
| Paper
| [[2018McLeod_MRCZ]]
| [[2020Beckers_FDR]]
| MRC Compression format
| Segmentation of the protein using False Discovery Rate (GUI)
|-  
|-  


| Paper
| Paper
| [[2018Zivanov_Relion3]]
| [[2020Farkas_MemBlob]]
| Relion 3
| Segmentation of membrane in membrane embedded proteins
|-  
|-  


| Paper
| Paper
| [[2020Caesar_Simple3]]
| [[2020Terashi_MainMastSeg]]
| Simple 3
| Segmentation of proteins into domains
|-  
|-  


| Paper
| Paper
| [[2021Baldwin_SCF]]
| [[2022Ranno_Neural]]
| Visualizer of the Sampling Compensation Factor
| Neural representation of a map
|-  
|-  


| Paper
| Paper
| [[2021Maji_BlackBox]]
| [[2021He_EMNUSS]]
| Exploration of image processing concepts
| EMNUSS: Identification of secondary structure in CryoEM maps with deep learning
|-  
|-  


| Paper
| Paper
| [[2021Sharov_Relion]]
| [[2024Sazzed_CryoSSESeg]]
| Use of Relion within Scipion
| CryoSSESeg: Identification of secondary structure in CryoEM maps with deep learning
|-  
|-  


| Paper
| Paper
| [[2021Sorzano_Scipion]]
| [[2025Cao_EMInfo]]
| Use of Scipion as a way to compare the results of multiple methods
| EMInfo: Segmentation of secondary structure and nucleic acids in CryoEM maps
|-
 
| Paper
| [[2021Strelak_Xmipp]]
| Advances in Xmipp
|-  
|-  


|}
|}


== Electron tomography ==
=== Fitting and docking ===
 
=== Image preprocessing ===


{|
{|


| Paper
| Paper
| [[2015Yan_thickness]]
| [[1999Volkmann_Fitting]]
| Determination of thickness, tilt and electron mean free path
| Fitting in real space
|-  
|-  


| Paper
| Paper
| [[2018Wu_contrast]]
| [[2001Baker_Review]]
| Contrast enhancement to improve alignability
| Review of protein structure prediction
|-  
|-  


|}
| Paper
 
| [[2001Jones_Review]]
=== Image alignment ===
| Review of protein structure prediction
 
|-
{|


| Paper
| Paper
| [[1982Guckenberger_commonOrigin]]
| [[2003Kovacs_FRM3D]]
| Determination of a common origin in the micrographs of titl series in three-dimensional electron microscopy
| Fast Rotational Alignment of two EM maps
|-  
|-  


| Paper
| Paper
| [[1992Lawrence_leastSquares]]
| [[2004Tama_NMA1]]
| Least squares solution of the alignment problem
| Flexible fitting with Normal Modes (I)
|-  
|-  


| Paper
| Paper
| [[1995Penczek_dual]]
| [[2004Tama_NMA2]]
| Dual tilt alignment
| Flexible fitting with Normal Modes (II)
|-  
|-  


| Paper
| Paper
| [[1996Owen_alignmentQuality]]
| [[2005Velazquez_Superfamilies]]
| Automatic alignment without fiducial markers and evaluation of alignment quality
| Recognition of the superfamily folding in medium-high resolution volumes
|-  
|-  


| Paper
| Paper
| [[1998Grimm_normalization]]
| [[2007DeVries_Haddock]]
| Discussion of several gray level normalization methods for electron tomography
| Docking with Haddock 2.0
|-  
|-  


| Paper
| Paper
| [[2001Brandt_Automatic1]]
| [[2007Kleywegt_QualityControl]]
| Automatic alignment without fiducial markers
| Quality control and validation of fitting
|-  
|-  


| Paper
| Paper
| [[2001Brandt_Automatic2]]
| [[2008Orzechowski_Flexible]]
| Automatic alignment with fiducial markers
| Flexible fitting with biased molecular dynamics
|-  
|-  


| Paper
| Paper
| [[2006Winkler_alignment]]
| [[2008Rusu_Interpolation]]
| Marker-free alignment and refinement
| Biomolecular pleiomorphism probed by spatial interpolation of coarse models
|-  
|-  


| Paper
| Paper
| [[2006Castano_alignment]]
| [[2012Biswas_Secondary]]
| Alignment with non-perpendicularity
| Secondary structure determination in EM volumes
|-
|-  


| Paper
| Paper
| [[2007Castano_alignment]]
| [[2012Velazquez_Constraints]]
| Fiducial-less alignment of cryo-sections
| Multicomponent fitting by using constraints from other information sources
|-  
|-  


| Paper
| Paper
| [[2009Sorzano_alignment]]
| [[2013Chapman MS_Atomicmodeling]]
| Marker-free alignment and refinement
| Atomic modeling of cryo-electron microscopy reconstructions--joint refinement of model and imaging parameters
|-  
|-  


| Paper
| Paper
| [[2010Cantele_dualAlignment]]
| [[2013Esquivel_Modelling]]
| Alignment of dual series
| Review on modelling (secondary structure, fitting, ...)
|-  
|-  


| Paper
| Paper
| [[2014Tomonaga_Automatic]]
| [[2013Lopez_Imodfit]]
| Automatic alignment of tilt series using the projection themselves
| Fitting based on vibrational analysis
|-  
|-  


| Paper
| Paper
| [[2014Han_Automatic]]
| [[2013Nogales_3DEMLoupe]]
| Automatic alignment of tilt series using SIFT features
| Normal Mode Analysis of reconstructed volumes
|-  
|-  


| Paper
| Paper
| [[2015Han_Automatic]]
| [[2014AlNasr_Secondary]]
| Automatic alignment of tilt series using fiducials
| Identification of secondary structure elements in EM volumes
|-  
|-  


| Paper
| Paper
| [[2017Mastronarde_Automatic]]
| [[2014Politis_MassSpect]]
| Automatic alignment and reconstruction of tilt series in IMOD
| Integration of mass spectroscopy information
|-  
|-  


| Paper
| Paper
| [[2018Fernadez_Beam]]
| [[2014Rey_MassSpect]]
| Image alignment considering beam induced motion
| Integration of mass spectroscopy information
|-  
|-  


| Paper
| Paper
| [[2018Han_Fast]]
| [[2014Villa_Review]]
| Automatic alignment using fiducial markers
| Review of atomic fitting into EM volumes
|-  
|-  


| Paper
| Paper
| [[2019Fernandez_residual]]
| [[2015Barad_EMRinger]]
| Alignment of tilt series using residual interpolation
| Validation of hybrid models
|-  
|-  


| Paper
| Paper
| [[2019Han_Dual]]
| [[2015Bettadapura_PF2Fit]]
| Automatic alignment using fiducial markers in dual tilt series
| Fast rigid fitting of PDBs into EM maps
|-  
|-  


| Paper
| Paper
| [[2020Sorzano_automatic]]
| [[2015Carrillo_CapsidMaps]]
| Automatic alignment considering several geometrical distortions
| Analysis of virus capsids using Google Maps
|-  
|-  


| Paper
| Paper
| [[2021Han_LocalConstraints]]
| [[2015Hanson_Continuum]]
| Automatic alignment considering local constraints
| Modelling assemblies with continuum mechanics
|-  
|-  


|}
| Paper
 
| [[2015Lopez_Review]]
=== CTF estimation and restoration ===
| Review of structural modelling from EM data
 
|-
{|


| Paper
| Paper
| [[2003Winkler_CTF]]
| [[2015Schroeder_Hybrid]]
| Focus gradient correction in electron tomography
| Review on model building
|-  
|-  


| Paper
| Paper
| [[2006Fernandez_CTF]]
| [[2015Tamo_Dynamics]]
| CTF determination and correction in electron tomography
| Dynamics in integrative modeling
|-  
|-  


| Paper
| Paper
| [[2009Zanetti_CTF]]
| [[2015Sorzano_AtomsToVoxels]]
| CTF determination and correction in electron tomography
| Accurate conversion of an atomic model into a voxel density volume
|-  
|-  


| Paper
| Paper
| [[2009Xiong_CTF]]
| [[2016Joseph_Evolution]]
| CTF determination and correction for low dose tomographic tilt series
| Evolutionary constraints for the fitting of atomic models into density maps
|-  
|-  


| Paper
| Paper
| [[2012Eibauer_CTF]]
| [[2016Joseph_Refinement]]
| CTF determination and correction
| Refinement of atomic models in high-resolution EM reconstructions using Flex-EM
|-  
|-  


| Paper
| Paper
| [[2015Bharat_CTFCorrectedSubtomogramAveraging]]
| [[2016Murshudov_Refinement]]
| Subtomogram averaging with CTF correction using a Bayesian prior
| Refinement of atomic models in high-resolution EM reconstructions
|-  
|-  


| Paper
| Paper
| [[2017Turonova_3DCTF]]
| [[2016Segura_3Diana]]
| 3D CTF Correction
| Validation of hybrid models
|-  
|-  


| Paper
| Paper
| [[2017Kunz_3DCTF]]
| [[2016Singharoy_MDFF]]
| 3D CTF Correction
| Construction of hybrid models driven by EM density and molecular dynamics
|-  
|-  
|}
=== 3D reconstruction ===
{|


| Paper
| Paper
| [[1972Gilbert_SIRT]]
| [[2016Wang_Rosetta]]
| Simultaneous Iterative Reconstruction Technique (SIRT)
| Construction of hybrid models driven by EM density using Rosetta
|-  
|-  


| Paper
| Paper
| [[1973Herman_ART]]
| [[2017Chen_CoarseGraining]]
| Algebraic Reconstruction Technique (ART)
| Coarse graining of EM volumes
|-  
|-  


| Paper
| Paper
| [[1984Andersen_SART]]
| [[2017Joseph_Metrics]]
| Simultaneous Algebraic Reconstruction Technique (SART)
| Metrics analysis for the comparison of structures
|-  
|-  


| Paper
| Paper
| [[1992Radermacher_WBP]]
| [[2017Hryc_WeightedAtoms]]
| Weighted Backprojection in electron tomography
| Construction of hybrid models by locally weighting the different atoms
|-  
|-  


| Paper
| Paper
| [[1997Marabini_reconstruction]]
| [[2017Matsumoto_Distribution]]
| Iterative reconstruction in electron tomography
| Estimating the distribution of conformations of atomic models
|-  
|-  


| Paper
| Paper
| [[2002Fernandez_reconstruction]]
| [[2017Michel_ContactPrediction]]
| Iterative reconstruction in electron tomography
| Structure prediction by contact prediction
|-  
|-  


| Paper
| Paper
| [[2007Radermacher_WBP]]
| [[2017Miyashita_EnsembleFitting]]
| Weighted Backprojection in electron tomography
| Ensemble fitting using Molecular Dynamics
|-  
|-  


| Paper
| Paper
| [[2008Fernandez_CARP]]
| [[2017Turk_ModelBuilding]]
| Component Averaged Row Projections (CARP)
| Tutorial on model building and protein visualization
|-  
|-  


| Paper
| Paper
| [[2010Xu_Long]]
| [[2017Wang_PartialCharges]]
| Iterative reconstructions with long object correction and GPU implementation
| Appearance of partial charges in EM maps
|-  
|-  


| Paper
| Paper
| [[2012Herman General Superiorization]]
| [[2017Wlodawer]]
| Superiorization: an optimization heuristic for medical physics
| Comparison of X-ray and EM high resolution structures
|-  
|-  


| Paper
| Paper
| [[2012Zhang_IPET_FETR]]
| [[2018Cassidy_review]]
| IPET and FETR, a reconstruction algorithm for single molecule tomography
| Review of methods for hybrid modeling
|-  
|-  


| Paper
| Paper
| [[2013Goris_SIRT_TV_DART]]
| [[2018Chen_SudeChains]]
| Combination of SIRT, Total Variation and Discrete ART to reconstruct and segment at the same time
| A comparison of side chains between X-ray and EM maps
|-  
|-  


| Paper
| Paper
| [[2013Briegel A_Challenge]]
| [[2018Kawabata_Pseudoatoms]]
| The challenge of determining handedness in electron tomography and the use of DNA origami gold nanoparticle helices as molecular standards
| Modelling the EM map with Gaussian pseudoatoms
|-  
|-  


| Paper
| Paper
| [[2013Messaoudi_EnergyFiltered]]
| [[2018Kovacs_Medium]]
| 3D Reconstruction of Energy-Filtered TEM
| Modelling of medium resolution EM maps
|-  
|-  


| Paper
| Paper
| [[2014Paavolainen_Missing]]
| [[2018Neumann_validation]]
| Compensation of the missing wedge
| Validation of fitting, resolution assessment and quality of fit
|-  
|-  


| Paper
| Paper
| [[2015Venkatakrishnan_MBIR]]
| [[2018Terwilliger_map_to_model]]
| 3D Reconstruction with priors
| Phenix map_to_model, automatic modelling of EM volumes
|-  
|-  


| Paper
| Paper
| [[2016Deng_ICON]]
| [[2018Wang_MD]]
| 3D Reconstruction with missing information restoration
| Constructing atomic models using molecular dynamics
|-  
|-  


| Paper
| Paper
| [[2016Guay_Compressed]]
| [[2018Xia_MVPENM]]
| 3D Reconstruction using compressed sensing
| Multiscale Normal Mode Analysis
|-  
|-  


| Paper
| Paper
| [[2016Turonova_Artifacts]]
| [[2018Yu_Atomic]]
| Artifacts observed during 3D reconstruction
| Constructing atomic models using existing tools
|-  
|-  


| Paper
| Paper
| [[2019Yan_MBIR]]
| [[2019Bonomi_Multiscale]]
| 3D Reconstruction with priors and demonstration of its use in biological samples
| Bayesian multi-scale modelling
|-  
|-  


| Paper
| Paper
| [[2020Sanchez_Hybrid]]
| [[2019Kidmose_Namdinator]]
| 3D reconstruction with a special acquisition and alignment scheme
| Namdinator: Flexible fitting with NAMD
|-  
|-  


| Paper
| Paper
| [[2020Song_Tygress]]
| [[2019Kim_CryoFit]]
| 3D reconstruction with a special acquisition and alignment scheme
| CryoFit: flexible fitting in Phoenix
|-  
|-  


| Paper
| Paper
| [[2021Fernandez_TomoAlign]]
| [[2019Klaholz_Review]]
| 3D reconstruction with sample motion and CTF correction
| Review of Phenix tools to modelling
|-
|-  


| Paper
| Paper
| [[2021Geng_Nudim]]
| [[2019Subramaniya_DeepSSE]]
| Non-uniform FFT reconstruction and total variation to fill the missing wedge
| Secondary structure prediction from maps using deep learning
|-
|-  
 
|}
 
=== Noise reduction ===
{|


| Paper
| Paper
| [[2001Frangakis_NAD]]
| [[2019Zhang_CoarseGrained]]
| Noise reduction with Nonlinear Anisotropic Diffusion
| Coarse-graining of EM maps
|-  
|-  


| Paper
| Paper
| [[2003Fernandez_AND]]
| [[2020Costa_MDeNM]]
| Anisotropic nonlinear diffusion for electron tomography
| Flexible fitting with molecular dynamics and normal modes
|-  
|-  


| Paper
| Paper
| [[2003Jiang_Bilateral]]
| [[2020Cragnolini_Tempy2]]
| Bilateral denoising filter in electron microscopy
| TEMpy2 library for density-fitting and validation
|-  
|-  


| Paper
| Paper
| [[2005Fernandez_AND]]
| [[2020Dodd_ModelBuilding]]
| Anisotropic nonlinear denoising in electron tomography
| Model building possibilities, with special emphasis on flexible fitting
|-  
|-  


| Paper
| Paper
| [[2007Heide_median]]
| [[2020Ho_CryoID]]
| Iterative median filtering in electron tomography
| Identification of proteins in structural proteomics from cryoEM volumes
|-
|-  


| Paper
| Paper
| [[2007Fernandez_autAND]]
| [[2020Hoh_Buccaneer]]
| Anisotropic nonlinear diffusion with automated parameter tuning
| Structure modelling with Buccaneer
|-
|-  
 


| Paper
| Paper
| [[2009Fernandez_Beltrami]]
| [[2020Joseph_comparison]]
| Nonlinear filtering based on Beltrami flow
| Comparison of map and model, or two maps
|-  
|-  
 
| Paper
| Paper
| [[2010Bilbao_MeanShift]]
| [[2020Kim_Review]]
| Mean Shift Filtering
| Review of the options for atomic modelling
|-  
|-  


| Paper
| Paper
| [[2014Kovacik_wedgeArtefacts]]
| [[2020Leelananda_Constraints]]
| Removal of wedge artefacts
| NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD structure refinement
|-  
|-  


| Paper
| Paper
| [[2014Maiorca_beadArtefacts]]
| [[2020Liebschner_Ceres]]
| Removal of gold bead artefacts
| CERES: Web server of refined atomic maps of CryoEM deposited maps by Phenix
|-  
|-  


| Paper
| Paper
| [[2018Trampert_Inpainting]]
| [[2020Oroguchi]]
| Removal of the missing wedge by inpainting
| Assessment of Force Field Accuracy Using Cryogenic Electron Microscopy Data
|-  
|-  


| Paper
| Paper
| [[2018Moreno_TomoEED]]
| [[2020Vant_Flexible]]
| Fast Anisotropic Diffusion
| Flexible fitting with molecular dynamics and neural network potentials
|-  
|-  


| Paper
| Paper
| [[2018Wu_Enhancement]]
| [[2021Behkamal_Secondary]]
| Enhancing the image contrast of electron tomography
| Secondary structure from medium resolution maps
|-  
|-  


|}
| Paper
 
| [[2021Chojnowski_quality]]
=== Segmentation ===
| Quality of models automatically fitted with ARP/wARP
 
|-
{|


| Paper
| Paper
| [[2002Frangakis_Eigenanalysis]]
| [[2021Han_Vesper]]
| Segmentation using eigenvector analysis.
| VESPER: global and local cryo-EM map alignment using local density vectors
|-  
|-  


| Paper
| Paper
| [[2002Volkmann_Watershed]]
| [[2021Lawson_Challenge]]
| Segmentation using watershed transform.
| Validation recommendations based on outcomes of the 2019 EMDataResource challenge
|-  
|-  


| Paper
| Paper
| [[2003Bajaj_BoundarySegmentation]]
| [[2021Mori_Flexible]]
| Segmentation based on fast marching.
| Efficient Flexible Fitting Refinement with Automatic Error Fixing
|-
|-  


| Paper
| Paper
| [[2005Cyrklaff_Thresholding]]
| [[2021Pfab_DeepTracer]]
| Segmentation using optimal thresholding.
| DeepTracer for fast de novo cryo-EM protein structure modeling
|-  
|-  


| Paper
| Paper
| [[2007Lebbink_TemplateMatching]]
| [[2021Saltzberg_IMP]]
| Segmentation using template matching.
| Using the Integrative Modeling Platform to model a cryoEM map
|-  
|-  


| Paper
| Paper
| [[2007Sandberg_OrientationFields]]
| [[2021Terwilliger_CryoID]]
| Segmentation using orientation fields.
| Identification of sequence in a CryoEM map from a set of candidates
|-  
|-  


| Paper
| Paper
| [[2007Sandberg_SegmentationReview]]
| [[2021Titarenko_LocalCorr]]
| Review on segmentation in electron tomography.
| Performance improvement of local correlation for docking
|-  
|-  


| Paper
| Conference
| [[2008Garduno_FuzzySegmentation]]
| [[2021Vuillemot_NMA]]
| Segmentation using fuzzy set theory principles.
| Flexible fitting using a combined Bayesian and Normal Mode approach with Hamiltonian Monte Carlo sampling
|-  
|-  


| Paper
| Paper
| [[2009Lebbink_TemplateMatching2]]
| [[2022Antanasijevic_ab]]
| Segmentation using template matching.
| Sequence determination of antibodies bound to a map
|-  
|-  


| Paper
| Paper
| [[2012RubbiyaAli_EdgeDetection]]
| [[2022Behkamal_LPTD]]
| Parameter-Free Segmentation of Macromolecular Structures.
| LPTD: Topology determination of CryoEM maps
|-  
|-  


| Conference
| Paper
| [[2015Xu_TemplateMatching]]
| [[2022Bouvier_coevolution]]
| Detection of macromolecular complexes with a reduced representation of the templates.
| Atomic modelling exploiting residue coevolution
|-  
|-  


| Paper
| Paper
| [[2017Ali_RAZA]]
| [[2022Chojnowski_findMySeq]]
| Automated segmentation of tomograms
| Identify sequence in CryoEM map using Deep Learning
|-  
|-  


| Paper
| Paper
| [[2017Chen_Annotation]]
| [[2022Hryc_Pathwalking]]
| Automated annotation of tomograms
| Atomic modelling with Pathwalking
|-  
|-  


| Paper
| Paper
| [[2017Tasel_ActiveContours]]
| [[2022He_EMBuild]]
| Segmentation with active contours
| Atomic modelling for complexes with EMbuild
|-  
|-  


| Paper
| Paper
| [[2017Xu_DeepLearning]]
| [[2022Krieger_Prody2]]
| Finding proteins in tomograms using deep learning
| Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0
|-  
|-  


| Paper
| Paper
| [[2018Zeng_DeepLearning]]
| [[2022Neijenhuis_Haddock]]
| Mining features in Electron Tomography by deep learning
| Protein-protein interface refinement in complex maps with Haddock2.4
|-  
|-  


| Paper
| Paper
| [[2020Salfer_PyCurv]]
| [[2022Terwilliger_AlphaFold]]
| Curvature analysis of segmented tomograms
| Iterative modelling with AlphaFold and experimental maps
|-  
|-  


| Paper
| Paper
| [[2021Dimchev_filaments]]
| [[2022Urzhumtsev_Direct]]
| Segmentation of filaments in tomograms
| Calculation of the EM map from an atomic model
|-  
|-  


|}
| Paper
 
| [[2022Urzhumtsev_XrayEM]]
=== Resolution ===
| Effect of the local resolution on the atomic modeling
{|
|-


| Paper
| Paper
| [[2005Cardone_Resolution]]
| [[2022Vuillemot_NMMD]]
| Resolution criterion for electron tomography
| NMMD: Flexible fitting with simultaneous Normal Mode and Molecular Dynamics displacements
|-  
|-  


| Chapter
| Paper
| [[2007Penczek_Resolution]]
| [[2022Zhang_CRITASSER]]
| Review of resolution criteria for electron tomography
| Atomic models of assemble protein structures with deep learning
|-  
|-  


| Paper
| Paper
| [[2015Diebolder_ConicalFSC]]
| [[2023Blau_FittingML]]
| Conical Fourier Shell Correlation
| Maximum-likelihood fitting of atomic models in EM maps
|-  
|-  


| Paper
| Paper
| [[2020Vilas_Monotomo]]
| [[2023Chang_CryoFold]]
| Resolution determination in tomograms
| Flexible fitting into cryo-EM maps with CryoFold (a MELD plugin)
|-
|-  
 
|}
 
=== Subtomogram analysis ===
 
{|


| Paper
| Paper
| [[2000Bohm_Template]]
| [[2023Dai_CryoFEM]]
| Macromolecule finding by template matching
| CryoFEM: Deep learning+AlphaFold 2 for the interpretation of maps
|-  
|-  


| Paper
| Paper
| [[2002Frangakis_Template]]
| [[2023Millan_LL]]
| Macromolecule finding by template matching
| Likelihood-based docking of models into cryo-EM maps
|-  
|-  


| Paper
| Paper
| [[2006Nickell_Review]]
| [[2023Park_CSA]]
| Review of macromolecule finding by template matching (Visual Proteomics)
| Atomic model fitting using conformational space annealing
|-  
|-  


| Paper
| Paper
| [[2007Best_Review]]
| [[2023Read_LL]]
| Review of Localization of Protein Complexes by Pattern Recognition
| Likelihood-based signal and noise analysis for docking of models into cryo-EM maps
|-  
|-  


| Paper
| Paper
| [[2007Forster_Review]]
| [[2023Reggiano_MEDIC]]
| Review of structure determination by subtomogram averaging
| Evaluation of atomic models using MEDIC
|-
|-  


| Paper
| Paper
| [[2008Forster_Classification]]
| [[2023Richardson_Overfitting]]
| Classification of subtomograms using constrained correlation
| Evaluation of overfitting errors in model building
|-
|-  


| Paper
| Paper
| [[2008Bartesaghi_Classification]]
| [[2023Sweeney_ChemEM]]
| Classification and averaging of subtomograms
| ChemEM: Flexible Docking of Small Molecules in Cryo-EM Structures
|-
|-  


| Paper
| Paper
| [[2008Schmid_Averaging]]
| [[2023Terashi_DAQrefine]]
| Alignment and averaging of subtomograms
| Atomic model refinement using AlphaFold2 and DAQ
|-
|-  


| Paper
| Paper
| [[2010Amat_Averaging]]
| [[2023Terashi_DeepMainMast]]
| Alignment and averaging of subtomograms exploiting thresholding in Fourier space
| DeepMainMast: de novo modelling of CryoEM maps
|-
|-  


| Paper
| Paper
| [[2010Yu_PPCA]]
| [[2023Terwilliger_AlphaFold]]
| Probabilistic PCA for volume classification
| Comparison of AlphaFold predictions with experimental maps and models
|-
|-  


| Paper
| Paper
| [[2013Chen_Averaging]]
| [[2023Wang_CryoREAD]]
| Fast alignment of subtomograms using spherical harmonics
| CryoREAD: de novo modelling of nucleic acids
|-
|-  


| Paper
| Paper
| [[2013Kuybeda_Averaging]]
| [[2024Beton_Ensemble]]
| Alignment and averaging of subtomograms using the nuclear norm of the cluster
| Ensemble fitting
|-
|-  


| Paper
| Paper
| [[2013Shatsky_Averaging]]
| [[2024Chen_EModelX]]
| Alignment and averaging of subtomograms with constrained cross-correlation
| Atomic modelling de novo from cryoEM maps
|-
|-  


| Paper
| Paper
| [[2013Yu_Projection]]
| [[2024Dahmani_MDFF]]
| Subtomogram averaging by aligning their projections
| Accelerated MDFF flexible fitting
|-
|-  


| Paper
| Paper
| [[2014Chen_Autofocus]]
| [[2024Giri_CryoStruct]]
| Subtomogram averaging and classification with special attention to differences
| CryoStruct: de novo modeling of cryoEM maps
|-
|-  


| Paper
| Paper
| [[2014Yu_ReferenceBias]]
| [[2024Gucwa_CMM]]
| Scoring the reference bias
| CheckMyMetal: Metal analysis in CryoEM maps
|-
|-  


| Paper
| Paper
| [[2014Voortman_LimitingFactors]]
| [[2024Jamali_Modelangelo]]
| Limiting factors of subtomogram averaging
| ModelAngelo: Automated model building of cryoEM maps
|-
|-  


| Paper
| Paper
| [[2015Bharat_CTFCorrectedSubtomogramAveraging]]
| [[2024He_SHOT]]
| Subtomogram averaging with CTF correction using a Bayesian prior
| Accurate global and local 3D alignment of cryo-EM density maps using local spatial structural features
|-  
|-  


| Paper
| Paper
| [[2015Yu_ReferenceBias]]
| [[2024Hoff_EMMIVox]]
| Scoring the reference bias
| EMMIVox: Model fitting using ensembles and molecular dynamics
|-
|-  


| Paper
| Paper
| [[2016Bharat_Relion]]
| [[2024Li_EMRNA]]
| Subtomogram averaging with Relion
| EMRNA: de novo modeling of RNA structures
|-
|-  


| Paper
| Paper
| [[2016Song_MatrixNorm]]
| [[2024Li_EM2NA]]
| Matrix norm minimization for tomographic reconstruction and alignment
| EM2NA: Detection and de novo modelling of nucleic acids in cryoEM maps
|-
|-  


| Paper
| Paper
| [[2017Castano_ParticlePicking]]
| [[2024Read_Interactive]]
| Particle picking in tomograms for subtomogram averaging
| Interactive local docking
|-
|-  


| Paper
| Paper
| [[2017Frazier_Tomominer]]
| [[2024Wang_DiffModeller]]
| TomoMiner a software platform for large-scale subtomogram analysis
| CryoEM map modelling integrating AlphaFold2 and diffusion networks
|-
|-  


| Paper
| Paper
| [[2018Himes_emClarity]]
| [[2024Wankowicz_qFit]]
| emClarity for subtomogram averaging
| Multiconformer modeling of cryoEM maps
|-
|-  


| Paper
| Paper
| [[2018Zhao_Fast]]
| [[2024Wlodarski_cryoEnsemble]]
| Fast alignment and maximum likelihod for subtomogram averaging
| CryoEnsemble: cryoEM map interpretation with molecular dynamics simulated ensembles
|-
|-  


| Paper
| Paper
| [[2019Fokine_Enhancement]]
| [[2025Carr_Map2Seq]]
| Subtomogram enhancement through the locked self-rotation
| Map-to-sequence workflow
|-
|-  


| Paper
| Paper
| [[2019Han_Constrained]]
| [[2025Chen_CryoEvoBuilding]]
| Constrained reconstruction to enhance resolution
| CryoEvoBuilding: Model building for intermediate resolution maps using evolutionary information
|-
|-  


| Paper
| Paper
| [[2020Basanta_workflow]]
| [[2025Chen_GMMs]]
| Workflow for subtomogram averaging
| Model building in heterogeneous maps
|-
|-  


| Paper
| Paper
| [[2021Du_Active]]
| [[2025Haloi_Ligand]]
| Active learning to reduce the need of annotated samples
| Ligand detection in CryoEM maps using structure prediction and flexible fitting
|-
|-  


| Paper
| Paper
| [[2021Harastani_NMA]]
| [[2025Karolczak_Ligand]]
| Continuous flexibility analysis of subtomograms using normal modes
| Ligand detection in CryoEM maps using deep learning
|-
|-  


| Paper
| Paper
| [[2021Lucas_Cistem]]
| [[2025Li_EMProt]]
| Identification of particles in tomograms using Cistem
| EMProt: atomic modelling of cryoEM maps using deep learning
|-
|-  


| Paper
| Paper
| [[2021Scaramuzza_Dynamo]]
| [[2025Luo_DiffFit]]
| Subtomogram averaging workflow using Dynamo
| DiffFit: Flexible fitting of map and atomic model
|-
|-  


| Paper
| Paper
| [[2021Singla_Measures]]
| [[2025Mallet_crAI]]
| Analysis of different measures to analyze subtomogram clusters
| crAI: detection of antibodies in cryoEM maps
|-
|-  


| Paper
| Paper
| [[2021Tegunov_M]]
| [[2025Matsuoka_ForceConstant]]
| Image processing workflow for tilt-series (introduction of M)
| Empirical determination of the force constant for flexible fitting
|-
|-  


| Conference
| Paper
| [[2021Zeng_OpenSet]]
| [[2025Muenks_EmeraldID]]
| Unsupervised open set classification using deep learning
| Emerald ID: Identification of small ligands in cryoEM maps
|-
|-  


| Paper
| Paper
| [[2022Boehning_CompressedSensing]]
| [[2025Riahi_EMPOT]]
| Compressed sensing for subtomogram averaging
| EMPOT: aligning partially overlapping maps using Unbalanced Gromov-Wasserstein Divergence
|-
|-  


| Paper
| Paper
| [[2022Harastani_TomoFlow]]
| [[2025Shub_Mic]]
| Continuous flexibility analysis of subtomograms using 3D dense optical flow
| Mic: a deep learning algorithm to assign ions and waters in SPA maps
|-
|-  


|}
| Paper
 
| [[2025Su_CryoAtom]]
=== Single particle tomography ===
| CryoAtom: Model building using deep learning
 
|-
{|


| Paper
| Paper
| [[2012Bartesaghi_Constrained]]
| [[2025Wang_E3CryoFold]]
| 3D reconstruction by imposing geometrical constraints
| E3CryoFold: model building in cryoEM maps
|-
|-  


| Paper
| Paper
| [[2012Zhang_IPET_FETR]]
| [[2025Zhang_Emol]]
| FETR: a focused reconstruction algorithm for a single molecule 3D structure
| Emol: modeling protein-nucleic acid complex structures from cryo-EM maps
|-
|-  


| Paper
| Paper
| [[2015Galaz_SingleParticleTomography]]
| [[2025Zhang_Benchmark]]
| Set of tools for Single Particle Tomography in EMAN2
| Benchmarking multiple algorithms to compute an atomic model from a cryoEM map
|-  
|-  


| Paper
| Paper
| [[2016Galaz_SingleParticleTomography]]
| [[2025Zheng_Disorder]]
| Alignment algorithms and CTF correction
| Exploration of disordered regions in CryoEM maps
|-  
|-  
|}
=== Missing-wedge correction ===
{|


| Paper
| Paper
| [[2020Kovacs_Filaments]]
| [[2026Mulvaney_CASP16]]
| Removal of missing wedge artifacts in filamentous tomograms
| Relationship between local resolution, RMSF, pLDDT and SMOC in CASP16 CryoEM maps
|-  
|-  
| Paper
| [[2020Moebel_MCMC]]
| Missing wedge correction with Monte Carlo Markov Chains
|-
| Paper
| [[2020Zhai_LoTTor]]
| Missing-wedge correction by LoTTor ('''Lo'''w-'''T'''ilt '''T'''omographic 3D '''R'''econstruction for a single molecule structure)
|-


|}
|}


=== Molecular 3D dynamics  ===
=== Books and reviews ===


{|
{|


| Paper
| Book
| [[2015Zhang_IPET]]
| [[1980Herman_Tomography]]
| 3D structural fluctuation of macromoles)
| General book on tomography
|-
|-  


|}
| Book
| [[1988Kak_Tomography]]
| General book on tomography
|-


=== Books and reviews ===
| Paper
 
| [[2000Tao_Review]]
{|
| Review of single particles
|-


| Paper
| Paper
| [[2000Baumeister_Review]]
| [[2000VanHeel_Review]]
| Review of electron tomography
| Review of single particles
|-  
|-  


| Paper
| Paper
| [[2003Koster_Review]]
| [[2002Frank_Review]]
| Review of electron tomography
| Review of single particles
|-  
|-  


| Paper
| Paper
| [[2003Sali_Review]]
| [[2002Schmid_Review]]
| Review of electron tomography
| Review of single particles
|-  
|-  


Line 4,934: Line 4,956:


| Paper
| Paper
| [[2005Lucic_Review]]
| [[2004Subramaniam_Review]]
| Review of electron tomography
| Review of single particles
|-
 
| Paper
| [[2005Steven_Review]]
| Review of electron microscopy
|-  
|-  


Line 4,944: Line 4,971:


| Book
| Book
| [[2006Frank_TomoBook]]
| [[2006Frank_book]]
| Electron Tomography
| Book covering all aspects of electron microscopy of single particles
|-
 
| Paper
| [[2006Sorzano_Review]]
| Review of optimization problems in electron microscopy
|-  
|-  


| Book
| Paper
| [[2007McIntosh_Book]]
| [[2007Leschziner_Review]]
| Cellular Electron Microscopy
| Review of 3D heterogeneity handling algorithms
|-  
|-  


Line 4,960: Line 4,992:
| Paper
| Paper
| [[2008Fanelli_ImageFormation]]
| [[2008Fanelli_ImageFormation]]
| Review on the image formation model from the electron waves and open inverse-problems
| Review on the image formation model from the electron waves and open inverse-problems in Electron Tomography
|-  
|-  


Line 4,974: Line 5,006:


| Paper
| Paper
| [[2012Kudryashev_Review]]
| [[2008Mueller_Review]]
| Review of subtomogram averaging
| Review of Electron microscopy
|-  
|-  


| Paper
| Paper
| [[2013Briggs_Review]]
| [[2008Taylor_Review]]
| Review of subtomogram averaging
| Review of Electron microscopy
|-  
|-  


| Paper
| Paper
| [[2016Beck_Review]]
| [[2010DeRosier_Review]]
| Review of molecular sociology
| Personal account of how 3DEM developed in the early days
|-  
|-  


| Paper
| Chapter
| [[2016Ercius_Review]]
| [[2012Sorzano_Review]]
| Electron tomography for hard and soft materials research
| Review of single particle analysis using Xmipp
|-  
|-  


| Paper
| Chapter
| [[2017Galaz_Review]]
| [[2012Devaux_Protocol]]
| Review of single particle tomography
| Protocols for performing single particle analysis
|-  
|-  


| Paper
| Paper
| [[2017Plitzko_Review]]
| [[2014Bai_Review]]
| Review of electron tomography, FRET and FIB milling
| Recent advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[2019Schur_Review]]
| [[2015Carazo_Review]]
| Review of electron tomography and subtomogram averaging
| Review of the reconstruction process
|-  
|-  


| Paper
| Paper
| [[2021Frangakis_Review]]
| [[2015Cheng_Review]]
| Review of tomogram denoising in electron tomography
| A primer to Single Particle Cryo-EM
|-  
|-  


| Paper
| Paper
| [[2022Forster_Review]]
| [[2015Cheng_Reviewb]]
| Review of subtomogram averaging
| Single Particle Cryo-EM at crystallographic resolution
|-  
|-  
|}
=== Software ===
{|


| Paper
| Paper
| [[1996Kremer_IMOD]]
| [[2015Elmlund_Review]]
| IMOD
| Recent advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[1996Chen_Priism/IVE]]
| [[2015Henderson_Review]]
| Priism/IVE
| Recent advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[1996Frank_Spider]]
| [[2015Nogales_Review]]
| Spider
| Recent advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2015Schroeder_Review]]
| Xmipp
| Review of advances in the electron microscope
|-  
|-  


| Paper
| Paper
| [[2005Nickell_TOM]]
| [[2015VanDenBedem_Integrative]]
| TOM Toolbox
| Review of integrative structural biology
|-  
|-  


| Paper
| Paper
| [[2007Messaoudi_TomoJ]]
| [[2015Wu_Review]]
| TomoJ
| Review of advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[2008Heymann_BsoftTomo]]
| [[2016Carroni_CryoEM]]
| Bsoft
| Review of advances in Cryo-EM
|-  
|-  


| Paper
| Paper
| [[2012Zhang IPET FETR]]
| [[2016Egelman_CryoEM]]
| IPET
| Review of advances in Cryo-EM
|-  
|-  


| Paper
| Paper
| [[2015Ding_CaltechTomography]]
| [[2016Eisenstein_CryoEM]]
| Caltech tomography database
| News feature on the Method of the Year
|-  
|-  


| Paper
| Paper
| [[2015Noble_AppionProtomo]]
| [[2016FernandezLeiro_Review]]
| Batch fiducial-less tilt-series alignment in Appion using Protomo
| Review of EM
|-  
|-  


| Paper
| Paper
| [[2015vanAarle_Astra]]
| [[2016Glaeser_HowGood]]
| ASTRA Toolbox
| How good can cryo-EM become?
|-  
|-  


| Paper
| Paper
| [[2016Liu_FullMechTomo]]
| [[2016Jonic_PseudoAtoms]]
| Fully mechanically controlled automated electron microscopic tomography
| Review of the applications of the use of pseudoatoms in EM
|-
 
| Chapter
| [[2016Mio_Review]]
| Overview of the process to obtain EM reconstructions
|-  
|-  


| Paper
| Paper
| [[2017Han_AuTom]]
| [[2016Jonic_Review]]
| Software platform for Electron Tomography
| A review of computational ways to handle heterogeneity
|-  
|-  


| Paper
| Paper
| [[2017Wan_Simulator]]
| [[2016Nogales_Review]]
| Electron Tomography Simulator
| Review of advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[2021Burt_RWD]]
| [[2016Subramaniam_Review]]
| Interoperability between Relion, Warp M, and Dynamo
| Why cryo-EM is now suitable for crystallographic journals
|-  
|-  


| Paper
| Paper
| [[2022Ni_EmClarity]]
| [[2016Vinothkumar_Review]]
| Processing protocols with EmClarity
| Historical review and current limitations
|-  
|-  


|}
| Report
 
| [[2017Brezinski_Nobel]]
== 2D Crystals ==
| Scientific background on the Nobel Prize in Chemistry 2017
 
|-
=== 2D Preprocessing ===
 
{|


| Paper
| Paper
| [[1982Saxton_Averaging]]
| [[2017Cheng_review]]
| Radial Correlation Function
| Why CryoEM became so hot
|-  
|-  


| Paper
| Paper
| [[1984Saxton_Distortions]]
| [[2017Danev_Review]]
| 3D Reconstruction of distorted crystals
| Review of the use of phase plates in EM
|-  
|-  


| Paper
| Paper
| [[1986Henderson_Processing]]
| [[2017Elmlund_Review]]
| General 2D processing
| Review of the main current difficulties of EM
|-  
|-  


| Paper
| Paper
| [[2000He_PhaseAlignment]]
| [[2017Frank_Review]]
| Phase consistency and Alignment
| Historical review of EM
|-  
|-  


| Paper
| Paper
| [[2006Gil_Unbending]]
| [[2017Frank_TimeResolved]]
| Crystal unbending
| Review of time-resolved of EM
|-  
|-  


|}
| Paper
| [[2017Jonic_Review]]
| Review of computational methods to analyze conformational variability
|-


=== Classification ===
| Paper
{|
| [[2017Merino_DrugEM]]
| Applications of EM for drug design
|-


| Paper
| Paper
| [[1988Frank_Classification]]
| [[2017Rawson_Limitations]]
| MSA and classification in electron crystallography
| Limitations of EM for drug design
|-  
|-  


| Paper
| Paper
| [[1996Fernandez_SOM]]
| [[2017Sorzano_FourierProperties]]
| Classification based on self organizing maps
| Review of statistical properties of resolution measures defined in Fourier space
|-  
|-  


| Paper
| Paper
| [[1998Sherman_MSA]]
| [[2017Sorzano_SurveyIterative]]
| Classification based on MSA
| Survey of iterative reconstruction methods for EM
|-  
|-  
|}
=== 3D Reconstruction ===
{|


| Paper
| Paper
| [[1985Wang_Solvent]]
| [[2018Bruggeman_Crowdsourcing]]
| Solvent flattening
| Exploring crowdsourcing for EM image processing
|-  
|-  


| Paper
| Paper
| [[1990Henderson_Processing]]
| [[2018Cheng_Review]]
| General 3D processing
| Review of EM and future ahead
|-
|-  


| Paper
| Paper
| [[2004Marabini_ART]]
| [[2018Cossio_ML]]
| Algebraic Reconstruction Technique with blobs for crystals (Xmipp)
| Review of Maximum Likelihood methods
|-  
|-  


| Paper
| Paper
| [[2018Biyani_Badlu]]
| [[2018Grimes_Crystallography]]
| Image processing for badly ordered crystals
| Review of X-ray crystallography and its relationship to EM
|-  
|-  


|}
| Paper
 
| [[2018Murata_Review]]
=== Books and reviews ===
| Review of EM for structure dynamics
 
|-
{|


| Paper
| Paper
| [[1998Walz_Review]]
| [[2018Quentin_Biomedical]]
| Review of 2D crystallography
| Review of EM as a tool for biomedical research
|-  
|-  


| Paper
| Paper
| [[1999Glaeser_Review]]
| [[2018Scapin_DrugDiscovery]]
| Review of 2D crystallography
| Review of EM as a tool for drug discovery
|-  
|-  


| Paper
| Paper
| [[2001Ellis_Review]]
| [[2018Vilas_ImageProcessing]]
| Review of 2D crystallography
| Review of the recent developments in image processing for single particle analysis
|-  
|-  


| Paper
| Paper
| [[2001Glaeser_Review]]
| [[2018vonLoeffelholz_VPP]]
| Review of 2D crystallography
| Comparison of Volta Phase Plate reconstructions close to focus and with defocus
|-  
|-  


| Paper
| Paper
| [[2004Henderson_Review]]
| [[2018Eisenstein_DrugDesigners]]
| Review of electron microscopy
| Drug designers embrace cryo-EM
|-  
|-  


| Paper
| Paper
| [[2006Fernandez_Review]]
| [[2019Benjin_Review]]
| Review of single particles, electron tomography and crystallography
| Review of SPA
|-  
|-  


| Paper
| Paper
| [[2007Sorzano_Review]]
| [[2019Danev_Review]]
| Review of the image processing steps
| Review of future directions
|-  
|-  


|}
| Paper
| [[2019Lyumkis_Review]]
| Challenges and reviews
|-


=== Software ===
| Paper
| [[2019Sorzano_Review]]
| Review of continuous heterogeneity biophysics
|-


{|
| Paper
| [[2019Urzhumtseva_Review]]
| Review of rotation conventions
|-


| Paper
| Paper
| [[1996Crowther_MRC]]
| [[2020Abriata_Review]]
| MRC
| Considerations of structure prediction and CryoEM
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2020Akbar_Review]]
| Xmipp
| Review of membrane protein reconstructions
|-  
|-  


| Paper
| Paper
| [[2007Gipson_2dx]]
| [[2020Bendory_Review]]
| 2dx
| Review of image processing problems
|-  
|-  


| Paper
| Paper
| [[2007Heymann_Bsoft]]
| [[2020Dubach_Review]]
| Bsoft
| Review of resolution in X-ray crystallography and CryoEM
|-
 
| TechReport
| [[2020Lai_Statistics]]
| Review of statistical properties of image alignment
|-  
|-  


| Paper
| Paper
| [[2007Philippsen_IPLT]]
| [[2020Hu_Quaternions]]
| IPLT
| Review of the use of quaternions to describe rotations
|-  
|-  


|}
| Paper
| [[2020McCafferty_Review]]
| Review of SPA and Mass Spectroscopy
|-


== 3D Crystals - MicroED ==
| Paper
| [[2020Seffernick_Hybrid]]
| Review of hybrid (computational and experimental) methods to get protein structure
|-  


=== Sample Preparation ===
{|
| Paper
| Paper
| [[2016Shi_Preparation]]
| [[2020Nakane_Atomic]]
| Sample Preparation
| Single-particle cryo-EM at atomic resolution
|}
|-
=== Data Collection ===
{|
| Paper
| [[2014Nannenga_CR]]
| Continuous rotation
 
|}
=== Data Processing ===
{|


| Paper
| Paper
| [[2011Wisedchaisri_PhaseExtension]]
| [[2020Singer_Sigworth_Review]]
| Fragment-based phase extension
| Review of single particle analysis
|-
|-


| Paper
| Paper
| [[2015Hattne_Processing]]  
| [[2020Vilas_Review]]
| Data Processing
| Review of local resolution
|-
|-  
 
| Paper
| Paper
| [[2016Hattne_Correction]]
| [[2020Wigge_Review]]
| Image correction
| Review of drug discovery with CryoEM
|}
|-


=== Software ===
| Paper
{|
| [[2020Wu_Review]]
| Review of current limitations, with special emphasis on protein size
|-


| Paper
| Paper
| [[2014Iadanza_Processing]]
| [[2021Bai_Review]]
| Data Processing of still diffraction data
| Review of breakthroughs leading to atomic resolution
|}
 
=== Books and Reviews ===
{|
|  Paper
| [[2014Nannenga_Review ]]
| Review of MicroED
|-
|-


| Paper
| Paper
| [[2016Liu_Review ]]
| [[2021DImprima_Review]]
| Review of MicroED
| Review of sample preparation for single particle analysis
|-
|-


| Paper
| Paper
| [[2016Rodriguez_Review ]]
| [[2021Lander_Review]]
| Review of MicroED
| Review of focused analysis in SPA
|-  
|-


|}
| Paper
| [[2021Raimondi_Review]]
| General review of SPA
|-


== Helical particles ==
| Paper
| [[2022Beton_Fitting]]
| Review of fitting in SPA
|-


=== Filament picking ===
| Paper
| [[2022Burley_PDB]]
| Review of cryoEM derived structures at PDB
|-


{|
| Paper
| [[2022Caldraft_Tilt]]
| Review of applications of tilt pairs in SPA
|-


| Paper
| Paper
| [[2021Thurber_Automated]]
| [[2022Donnat_GAN]]
| Automated picking of filaments
| Review of Generative modelling with neural networks
|-  
|-


|}
| Paper
 
| [[2022Guaita_Review]]
=== Filament corrections ===
| Recent advances and current trends in cryo-electron microscopy
 
|-
{|


| Paper
| Paper
| [[1986Egelman_Curved]]
| [[2022Jones_Comment]]
| Algorithm for correcting curved filaments
| Comment on the impact of AlphaFold and next challenges ahead
|-  
|-


| Paper
| Paper
| [[1988Bluemke_Pitch]]
| [[2022Namba_Review]]
| Algorithm for correcting filaments with different helical pitches
| Review of the current state of SPA
|-  
|-


| Paper
| Paper
| [[2006Wang_Pitch]]
| [[2022Ourmazd_Comment]]
| Algorithm for correcting filaments with different helical pitches
| Comment on the impact of AlphaFold and next challenges ahead
|-  
|-


| Paper
| Paper
| [[2016Yang_Flexible]]
| [[2022Palmer_Local]]
| Algorithm for correcting filaments with flexible subunits
| Review of local methods in CryoEM
|-  
|-


| Paper
| Paper
| [[2019Ohashi_SoftBody]]
| [[2022Sorzano_1000]]
| Algorithm for correcting filaments with flexible helices
| CryoEM is the field of 1000+ methods
|-  
|-


|}
| Paper
| [[2022Subramaniam_Comment]]
| Comment on the impact of AlphaFold and next challenges ahead
|-


=== Reconstruction ===
| Paper
| [[2022Treder_DL]]
| Review of Deep Learning applications in CryoEM
|-


{|
| Paper
| [[2022Vant_MD]]
| Review of Molecular Dynamics analysis of CryoEM maps
|-


| Paper
| Paper
| [[1952Cochran_Fourier]]
| [[2023Amann_TimeResolved]]
| Fourier Bessel transform of filamentous structures
| Review of time-resolved cryoEM
|-  
|-


| Paper
| Paper
| [[1958Klug_Fourier]]
| [[2023Bai_Challenges]]
| Fourier Bessel decomposition of the projection images
| Challenges and opportunities in structure determination
|-  
|-


| Paper
| Paper
| [[1970DeRosier_Rec]]
| [[2023Beton_Fitting]]
| Image processing steps towards 3D reconstruction
| Review of fitting tools in cryoEM
|-  
|-


| Paper
| Paper
| [[1988Stewart_Rec]]
| [[2023DiIorio_AbInitio]]
| Image processing steps towards 3D reconstruction
| Review of ab initio reconstruction algorithms based on deep learning
|-  
|-


| Paper
| Paper
| [[1992Morgan_Rec]]
| [[2023Liu_AWI]]
| Image processing steps towards 3D reconstruction
| Review of the Air-Water Interface
|-  
|-


| Paper
| Paper
| [[2005Wang_Iterative]]
| [[2023Lucas_Structureome]]
| Iterative Fourier-Bessel algorithm
| Review of the localization of proteins and complexes in their cellular context
|-  
|-


| Paper
| Paper
| [[2007Egelman_Iterative]]
| [[2023Miyashita_MD]]
| Iterative real-space algorithm
| Review of the use of molecular dynamics in atomic modelling
|-  
|-


| Paper
| Paper
| [[2010Egelman_Pitfalls]]
| [[2023Si_DeNovo]]
| Pitfalls in helical reconstruction
| Review of the de-novo atomic modelling
|-  
|-


| Paper
| Paper
| [[2013Desfosses_Spring]]
| [[2023Tang_Conformational]]
| Helical processing with Spring
| Review of conformational heterogeneity and probability distributions
|-  
|-


| Paper
| Paper
| [[2015Zhang_seam]]
| [[2023Toader_Heterogeneity]]
| Workflow for the detection of the lattice seam
| Review of continuous heterogeneity
|-  
|-


| Paper
| Paper
| [[2016Rohou_Frealix]]
| [[2024Bock_MD]]
| Helical processing with Frealix
| Review of the joint use of Molecular Dynamics and CryoEM
|-  
|-


| Paper
| Paper
| [[2017_He]]
| [[2024Bowlby_Flexible]]
| Helical processing with Relion
| Review of continuous flexibility
|-  
|-


| Paper
| Paper
| [[2019_Pothula]]
| [[2024Cheng_Automated]]
| 3D Classification through 2D analysis
| Review of automated acquisition
|-  
|-


|}
| Paper
| [[2024Kimanius_Heterogeneity]]
| Review of heterogeneity analysis
|-


=== Validation ===
| Paper
| [[2024Lander_Validation]]
| Review of SPA validation
|-


{|
| Paper
| [[2024Riggi_Animation]]
| Review of 3D animation as a tool for integrative modeling
|-


| Paper
| Paper
| [[2014Egelman_ambiguity]]
| [[2025Farheen_Modeling]]
| How to detect incorrect models
| Review of structure modeling
|-  
|-


|}
| Paper
| [[2025Kim_Review]]
| Review of SPA and protein-protein or protein-ligand docking
|-


=== Books and reviews ===
| Paper
 
| [[2025Leone_Review]]
{|
| Review of the integration of Molecular Dynamics with experimental techniques
|-


| Paper
| Paper
| [[1970DeRosier_Rec]]
| [[2025Patwardhan_Extending]]
| Image processing steps towards 3D reconstruction
| Perspective on technological developments leading to a wider application of cryoEM
|-  
|-


| Paper
| Paper
| [[1992Morgan_Rec]]
| [[2025Wan_CryoETStandards]]
| Image processing steps towards 3D reconstruction
| Perspective on the need for CryoET standards
|-  
|-


| Paper
| Paper
| [[2004Henderson_Review]]
| [[2025Zhu_Quality]]
| Review of electron microscopy
| Review of AI-based quality assessment of SPA maps
|-
|-
 
| Paper
| [[2015Sachse_Review]]
| Review of the image processing steps in helical particles
|-
 
| Paper
| [[2021Egelman_Review]]
| Review of reconstruction problems in helical structures
|-  
 
| Paper
| [[2022Wang_Review]]
| Review of reconstruction problems in helical structures
|-  


|}
|}
Line 5,483: Line 5,532:


| Paper
| Paper
| [[1996Carragher_Phoelix]]
| [[1996Frank_Spider]]
| Phoelix
| Spider
|-  
|-  


| Paper
| Paper
| [[1996Crowther_MRC]]
| [[1996VanHeel_Imagic]]
| MRC
| Imagic
|-  
|-  


| Paper
| Paper
| [[1996Owen_Brandeis]]
| [[1999Lutdke_Eman]]
| Brandeis
| Eman
|-  
|-  
|}
== Icosahedral particles ==
=== Reconstruction ===
{|


| Paper
| Paper
| [[1970Crowther_Rec]]
| [[2004Sorzano_Xmipp]]
| Reconstruction of icosahedral viruses in Fourier space
| Xmipp
|-  
|-  


| Paper
| Paper
| [[1971Crowther_Rec]]
| [[2007Baldwin_AngularTransformations]]
| Reconstruction of icosahedral viruses in Fourier space
| The Transform Class in SPARX and EMAN2
|-  
|-  


| Paper
| Paper
| [[1996Fuller_Rec]]
| [[2007Heymann_Bsoft]]
| Reconstruction of icosahedral viruses in Fourier space
| Bsoft
|-  
|-  


| Paper
| Paper
| [[1997Thuman_Rec]]
| [[2007Grigorieff_Frealign]]
| Reconstruction of icosahedral viruses in Fourier space
| Frealign
|-  
|-  


| Paper
| Paper
| [[2019Goetschius_Asymmetric]]
| [[2008Scheres_XmippProtocols]]
| Approaches to reconstruct asymmetric features in viruses
| Xmipp Protocols
|-  
|-  


|}
| Paper
 
| [[2008Shaikh_SpiderProtocols]]
=== Classification ===
| Spider Protocols
 
|-
{|


| Paper
| Paper
| [[2005Scheres_Virus]]
| [[2012Wriggers_SitusConventions]]
| Classification of virus capsids in real space
| Conventions and workflows in Situs
|-  
|-  
|}
=== Books and reviews ===
{|


| Paper
| Paper
| [[1999Baker_Review]]
| [[2013DeLaRosa_Xmipp30]]
| Review of reconstruction of icosahedral viruses
| Xmipp 3.0
|-  
|-  


| Paper
| Paper
| [[1999Conway_Review]]
| [[2015Cianfrocco_Cloud]]
| Review of reconstruction of icosahedral viruses
| Software execution in the cloud
|-  
|-  


| Paper
| Paper
| [[2000Thuman_Review]]
| [[2015Cheng_MRC2014]]
| Review of reconstruction of icosahedral viruses
| Extensions to MRC file format
|-  
|-  


| Paper
| Paper
| [[2003Lee_Review]]
| [[2013DeLaRosa_Scipion]]
| Review of reconstruction of icosahedral viruses
| Scipion
|-  
|-  


| Paper
| Paper
| [[2003Navaza_Review]]
| [[2016Scheres_Relion]]
| Review of reconstruction of icosahedral viruses
| Tutorial on the use of Relion
|-  
|-  


| Paper
| Paper
| [[2006Grunewald_Review]]
| [[2016Grigorieff_Frealign]]
| Review of reconstruction of icosahedral viruses
| Tutorial on the use of Frealign
|-  
|-  


|}
| Paper
| [[2017Moriya_Sphire]]
| Tutorial on the use of Sphire
|-


=== Software ===
| Paper
| [[2018Bell_EMAN2]]
| New tools in EMAN2
|-


{|
| Paper
| [[2018Cianfrocco_cloud]]
| CryoEM Cloud Tools
|-


| Paper
| Paper
| [[1996Baker_EMPFT]]
| [[2018Grant_cisTEM]]
| EMPFT
| cisTEM
|-  
|-  


| Paper
| Paper
| [[1996Crowther_MRC]]
| [[2018McLeod_MRCZ]]
| MRC
| MRC Compression format
|-  
|-  


| Paper
| Paper
| [[1996Frank_Spider]]
| [[2018Zivanov_Relion3]]
| Spider
| Relion 3
|-  
|-  


| Paper
| Paper
| [[1996VanHeel_Imagic]]
| [[2020Caesar_Simple3]]
| Imagic
| Simple 3
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2021Baldwin_SCF]]
| Xmipp
| Visualizer of the Sampling Compensation Factor
|-  
|-  


| Paper
| Paper
| [[2013DeLaRosa_Xmipp30]]
| [[2021Jimenez_Scipion]]
| Xmipp 3.0
| Scipion workflow example for image processing
|-  
|-  


| Paper
| Paper
| [[2013Morin_Sliz SBGrid]]
| [[2021Kimanius_Relion4]]
| SBGrid presentation for eLife
| Changes in Relion 4.0
|-  
|-  


|}
| Paper
| [[2021Maji_BlackBox]]
| Exploration of image processing concepts
|-


== Liquid-cell TEM / in-situ TEM ==
| Paper
| [[2021Sharov_Relion]]
| Use of Relion within Scipion
|-  


 
| Paper
{|
| [[2021Sorzano_Scipion]]
| Use of Scipion as a way to compare the results of multiple methods
|-
 
| Paper
| [[2021Strelak_Xmipp]]
| Advances in Xmipp
|-
 
| Paper
| [[2022DiIorio_Multiple]]
| A Robust Single-Particle Cryo-Electron Microscopy (cryo-EM) Processing Workflow with cryoSPARC, RELION, and Scipion.
|-
 
| Paper
| [[2022Fluty_Precision]]
| Precision requirements and data compression
|-
 
| Paper
| [[2022Harastani_ContinuousFlex]]
| ContinuousFlex: Software for continuous heterogeneity analysis in cryo-EM and cryo-ET
|-
 
| Paper
| [[2022Warshamanage_EMDA]]
| A Python library for low-level computations such as local correlation
|-
 
| Paper
| [[2023Cheng_AutoEMage]]
| AutoEMage: a system for processing in streaming (SPA)
|-
 
| Paper
| [[2023Conesa_Scipion3]]
| Scipion3: A workflow engine for cryoEM
|-
 
| Paper
| [[2023Krieger_ScipionPrody]]
| Scipion-EM-Prody: Interface between Scipion and Prody (Structural Analysis)
|-
 
| Paper
| [[2023Matinyan_TRPX]]
| TRPX compression format
|-
 
| Paper
| [[2023Short_MRC2020]]
| MRC2020: improvements to Ximdisp and the MRC image-processing programs
|-
 
| Paper
| [[2024deLaRosa_EMHub]]
| A web-based Laboratory Information Management System for cryoEM facility
|-
 
| Paper
| [[2024Gonzalez_Dashboard]]
| A web-based dashboard for Relion
|-
 
| Paper
| [[2024Herre_Capsules]]
| SBGrid Capsules to execute programs in controlled environments
|-
 
| Paper
| [[2024Moriya_GoToCloud]]
| GoToCloud: SPA processing in the cloud
|-
 
| Paper
| [[2024Urzhumtseva_VUE]]
| VUE: Visualization of angular distributions
|-
 
| Paper
| [[2024Vuillemot_MDSPACE]]
| MDSpace and MDTomo to analyze continuous heterogeneity
|-
 
| Paper
| [[2025Chen_CryoCRAB]]
| CryoCRAB: a large database of curated micrographs
|-
 
| Conference
| [[2025Fu_T2Relion]]
| T2-Relion: Task-parallelism, Tensor-core acceleration of Relion
|-
 
| Paper
| [[2025Khoshbin_Magellon]]
| Magellon: a software platform for CryoEM image processing
|-
 
| Paper
| [[2025Matinyan_TRPX]]
| TRPX v2: fast compression of raw files
|-
 
|}
 
== Electron tomography ==
 
=== Data Collection ===
 
{|
 
| Paper
| [[2025Sharma_DataCollection]]
| Automation for cryo-electron tomography data collection
|-
 
|}
 
=== Image preprocessing ===
 
{|
 
| Paper
| [[2015Yan_thickness]]
| Determination of thickness, tilt and electron mean free path
|-
 
| Paper
| [[2018Wu_contrast]]
| Contrast enhancement to improve alignability
|-
 
|}
 
=== Image alignment ===
 
{|
 
| Paper
| [[1982Guckenberger_commonOrigin]]
| Determination of a common origin in the micrographs of titl series in three-dimensional electron microscopy
|-
 
| Paper
| [[1992Lawrence_leastSquares]]
| Least squares solution of the alignment problem
|-
 
| Paper
| [[1995Penczek_dual]]
| Dual tilt alignment
|-
 
| Paper
| [[1996Owen_alignmentQuality]]
| Automatic alignment without fiducial markers and evaluation of alignment quality
|-
 
| Paper
| [[1998Grimm_normalization]]
| Discussion of several gray level normalization methods for electron tomography
|-
 
| Paper
| [[2001Brandt_Automatic1]]
| Automatic alignment without fiducial markers
|-
 
| Paper
| [[2001Brandt_Automatic2]]
| Automatic alignment with fiducial markers
|-
 
| Paper
| [[2006Winkler_alignment]]
| Marker-free alignment and refinement
|-
 
| Paper
| [[2006Castano_alignment]]
| Alignment with non-perpendicularity
|-
 
| Paper
| [[2007Castano_alignment]]
| Fiducial-less alignment of cryo-sections
|-
 
| Paper
| [[2009Sorzano_alignment]]
| Marker-free alignment and refinement
|-
 
| Paper
| [[2010Cantele_dualAlignment]]
| Alignment of dual series
|-
 
| Paper
| [[2014Tomonaga_Automatic]]
| Automatic alignment of tilt series using the projection themselves
|-
 
| Paper
| [[2014Han_Automatic]]
| Automatic alignment of tilt series using SIFT features
|-
 
| Paper
| [[2015Han_Automatic]]
| Automatic alignment of tilt series using fiducials
|-
 
| Paper
| [[2017Mastronarde_Automatic]]
| Automatic alignment and reconstruction of tilt series in IMOD
|-
 
| Paper
| [[2018Fernadez_Beam]]
| Image alignment considering beam induced motion
|-
 
| Paper
| [[2018Han_Fast]]
| Automatic alignment using fiducial markers
|-
 
| Paper
| [[2019Fernandez_residual]]
| Alignment of tilt series using residual interpolation
|-
 
| Paper
| [[2019Han_Dual]]
| Automatic alignment using fiducial markers in dual tilt series
|-
 
| Paper
| [[2020Sorzano_automatic]]
| Automatic alignment considering several geometrical distortions
|-
 
| Paper
| [[2021Han_LocalConstraints]]
| Automatic alignment considering local constraints
|-
 
| Paper
| [[2022Ganguly_SparseAlign]]
| Sparse Align: Automatic detection of markers and deformation estimation
|-
 
| Paper
| [[2022Zheng_Aretomo]]
| Automatic alignment based on projection matching
|-
 
| Paper
| [[2024Coray_Automated]]
| Automated fiducial-based tilt series alignment in Dynamo
|-
 
| Paper
| [[2024deIsidro_deep]]
| Detection of tilt series misalignment in the reconstructed tomogram using a neural network
|-
 
| Paper
| [[2024Hou_Marker]]
| Marker detection using wavelets
|-
 
| Paper
| [[2024Xu_MarkerAuto2]]
| MarkerAuto2: Tilt series alignment using fiducials
|-
 
| Paper
| [[2025deIsidro_Misalignment]]
| Tilt series misalignment detection
|-
 
| Paper
| [[2025Guo_Alignment]]
| Tilt series alignment with L1-norm optimization
|-
 
|}
 
=== CTF estimation and restoration ===
 
{|
 
| Paper
| [[2003Winkler_CTF]]
| Focus gradient correction in electron tomography
|-
 
| Paper
| [[2006Fernandez_CTF]]
| CTF determination and correction in electron tomography
|-
 
 
| Paper
| [[2009Zanetti_CTF]]
| CTF determination and correction in electron tomography
|-
 
 
| Paper
| [[2009Xiong_CTF]]
| CTF determination and correction for low dose tomographic tilt series
|-
 
| Paper
| [[2012Eibauer_CTF]]
| CTF determination and correction
|-
 
| Paper
| [[2015Bharat_CTFCorrectedSubtomogramAveraging]]
| Subtomogram averaging with CTF correction using a Bayesian prior
|-
 
| Paper
| [[2017Turonova_3DCTF]]
| 3D CTF Correction
|-
 
| Paper
| [[2017Kunz_3DCTF]]
| 3D CTF Correction
|-
 
| Paper
| [[2024Mastronarded_CTFPlotter]]
| CTF estimation with CTFPlotter
|-
 
| Paper
| [[2024Zhang_CTFMeasure]]
| Simultaneous CTF estimation for a whole tilt series
|-
 
| Paper
| [[2025Khavnekar_PSD]]
| Accurate PSD determination in tilt series
|-
 
|}
 
=== 3D reconstruction ===
 
{|
 
| Paper
| [[1972Gilbert_SIRT]]
| Simultaneous Iterative Reconstruction Technique (SIRT)
|-
 
| Paper
| [[1973Herman_ART]]
| Algebraic Reconstruction Technique (ART)
|-
 
| Paper
| [[1984Andersen_SART]]
| Simultaneous Algebraic Reconstruction Technique (SART)
|-
 
| Paper
| [[1992Radermacher_WBP]]
| Weighted Backprojection in electron tomography
|-
 
| Paper
| [[1997Marabini_reconstruction]]
| Iterative reconstruction in electron tomography
|-
 
| Paper
| [[2002Fernandez_reconstruction]]
| Iterative reconstruction in electron tomography
|-
 
| Paper
| [[2007Radermacher_WBP]]
| Weighted Backprojection in electron tomography
|-
 
| Paper
| [[2008Fernandez_CARP]]
| Component Averaged Row Projections (CARP)
|-
 
| Paper
| [[2010Xu_Long]]
| Iterative reconstructions with long object correction and GPU implementation
|-
 
| Paper
| [[2012Herman General Superiorization]]
| Superiorization: an optimization heuristic for medical physics
|-
 
| Paper
| [[2012Zhang_IPET_FETR]]
| IPET and FETR, a reconstruction algorithm for a single particle structure determination without any averaging
|-
 
| Paper
| [[2013Goris_SIRT_TV_DART]]
| Combination of SIRT, Total Variation and Discrete ART to reconstruct and segment at the same time
|-
 
| Paper
| [[2013Briegel A_Challenge]]
| The challenge of determining handedness in electron tomography and the use of DNA origami gold nanoparticle helices as molecular standards
|-
 
| Paper
| [[2013Messaoudi_EnergyFiltered]]
| 3D Reconstruction of Energy-Filtered TEM
|-
 
| Paper
| [[2014Paavolainen_Missing]]
| Compensation of the missing wedge
|-
 
| Paper
| [[2015Venkatakrishnan_MBIR]]
| 3D Reconstruction with priors
|-
 
| Paper
| [[2016Deng_ICON]]
| 3D Reconstruction with missing information restoration
|-
 
| Paper
| [[2016Guay_Compressed]]
| 3D Reconstruction using compressed sensing
|-
 
| Paper
| [[2016Turonova_Artifacts]]
| Artifacts observed during 3D reconstruction
|-
 
| Paper
| [[2019Yan_MBIR]]
| 3D Reconstruction with priors and demonstration of its use in biological samples
|-
 
| Paper
| [[2020Sanchez_Hybrid]]
| 3D reconstruction with a special acquisition and alignment scheme
|-
 
| Paper
| [[2020Song_Tygress]]
| 3D reconstruction with a special acquisition and alignment scheme
|-
 
| Paper
| [[2021Fernandez_TomoAlign]]
| 3D reconstruction with sample motion and CTF correction
|-
 
| Paper
| [[2021Geng_Nudim]]
| Non-uniform FFT reconstruction and total variation to fill the missing wedge
|-
 
| Paper
| [[2024vanVeen_Missing]]
| Missing wedge filling in cryoET
|-
 
| Paper
| [[2025Debarnot_IceTide]]
| 3D Reconstruction in CryoET with local deformation corrections and neural networks
|-
 
|}
 
=== Noise reduction ===
{|
 
| Paper
| [[2001Frangakis_NAD]]
| Noise reduction with Nonlinear Anisotropic Diffusion
|-
 
| Paper
| [[2003Fernandez_AND]]
| Anisotropic nonlinear diffusion for electron tomography
|-
 
| Paper
| [[2003Jiang_Bilateral]]
| Bilateral denoising filter in electron microscopy
|-
 
| Paper
| [[2005Fernandez_AND]]
| Anisotropic nonlinear denoising in electron tomography
|-
 
| Paper
| [[2007Heide_median]]
| Iterative median filtering in electron tomography
|-
 
| Paper
| [[2007Fernandez_autAND]]
| Anisotropic nonlinear diffusion with automated parameter tuning
|-
 
| Paper
| [[2009Fernandez_Beltrami]]
| Nonlinear filtering based on Beltrami flow
|-
| Paper
| [[2010Bilbao_MeanShift]]
| Mean Shift Filtering
|-
 
| Paper
| [[2014Kovacik_wedgeArtefacts]]
| Removal of wedge artefacts
|-
 
| Paper
| [[2014Maiorca_beadArtefacts]]
| Removal of gold bead artefacts
|-
 
| Paper
| [[2018Trampert_Inpainting]]
| Removal of the missing wedge by inpainting
|-
 
| Paper
| [[2018Moreno_TomoEED]]
| Fast Anisotropic Diffusion
|-
 
| Paper
| [[2018Wu_Enhancement]]
| Enhancing the image contrast of electron tomography
|-
 
| Paper
| [[2022Liu_Isonet]]
| Isotropic reconstructions using deep learning
|-
 
| Paper
| [[2024vanBlerkom_GoldX]]
| GoldX: Gold bead removal
|-
 
| Paper
| [[2025Costa_CryoSamba]]
| CryoSamba: tomogram denoising
|-
 
|}
 
=== Segmentation ===
 
{|
 
| Paper
| [[2002Frangakis_Eigenanalysis]]
| Segmentation using eigenvector analysis.
|-
 
| Paper
| [[2002Volkmann_Watershed]]
| Segmentation using watershed transform.
|-
 
| Paper
| [[2003Bajaj_BoundarySegmentation]]
| Segmentation based on fast marching.
|-
 
| Paper
| [[2005Cyrklaff_Thresholding]]
| Segmentation using optimal thresholding.
|-
 
| Paper
| [[2007Lebbink_TemplateMatching]]
| Segmentation using template matching.
|-
 
| Paper
| [[2007Sandberg_OrientationFields]]
| Segmentation using orientation fields.
|-
 
| Paper
| [[2007Sandberg_SegmentationReview]]
| Review on segmentation in electron tomography.
|-
 
| Paper
| [[2008Garduno_FuzzySegmentation]]
| Segmentation using fuzzy set theory principles.
|-
 
| Paper
| [[2009Lebbink_TemplateMatching2]]
| Segmentation using template matching.
|-
 
| Paper
| [[2012RubbiyaAli_EdgeDetection]]
| Parameter-Free Segmentation of Macromolecular Structures.
|-
 
| Paper
| [[2014Martinez-Sanchez_TomoSegMemTV]]
| Membrane segmentation.
|-
 
| Conference
| [[2015Xu_TemplateMatching]]
| Detection of macromolecular complexes with a reduced representation of the templates.
|-
 
| Paper
| [[2017Ali_RAZA]]
| Automated segmentation of tomograms
|-
 
| Paper
| [[2017Chen_Annotation]]
| Automated annotation of tomograms
|-
 
| Paper
| [[2017Tasel_ActiveContours]]
| Segmentation with active contours
|-
 
| Paper
| [[2017Xu_DeepLearning]]
| Finding proteins in tomograms using deep learning
|-
 
| Paper
| [[2018Zeng_DeepLearning]]
| Mining features in Electron Tomography by deep learning
|-
 
| Paper
| [[2020Salfer_PyCurv]]
| Curvature analysis of segmented tomograms
|-
 
| Paper
| [[2021Dimchev_filaments]]
| Segmentation of filaments in tomograms
|-
 
| Paper
| [[2022Frangakis_Curvature]]
| Use of mean curvature for segmentation and visualization of tomograms
|-
 
| Paper
| [[2022Lamm_MemBrain]]
| Membrane segmentation using deep learning
|-
 
| Paper
| [[2023Sazzed_Struwwel]]
| Detection and analysis of filament networks
|-
 
| Paper
| [[2023Zeng_AITOM]]
| Structural pattern mining by unsupervised deep iterative subtomogram clustering
|-
 
| Paper
| [[2024Gao_DomainFit]]
| Protein identification in tomograms by mass spectroscopy, AlphaFold2 and domain fitting
|-
 
| Paper
| [[2024Khosrozadeh_CryoVesNet]]
| CryoVesNet: Vesicle segmentation in cryo-electron tomograms
|-
 
| Paper
| [[2024Last_Ais]]
| Ais: Interactive segmentation of tomograms
|-
 
| Paper
| [[2024Siggel_ColabSeg]]
| Interactive membrane segmentation of tomograms
|-
 
| Paper
| [[2025Chen_GCTransNet]]
| GCTransNet: Segmentation of mitochondrias in volume electron microscopy
|-
 
| Paper
| [[2025Morales_Membranes]]
| Membrane segmentation with a neural network
|-
 
| Paper
| [[2025Schoennenbeck_CryoVIA]]
| CryoVIA: An image analysis toolkit for the quantification of membrane structures
|-
 
|}
 
=== Resolution ===
{|
 
| Paper
| [[2005Cardone_Resolution]]
| Resolution criterion for electron tomography
|-
 
| Chapter
| [[2007Penczek_Resolution]]
| Review of resolution criteria for electron tomography
|-
 
| Paper
| [[2015Diebolder_ConicalFSC]]
| Conical Fourier Shell Correlation
|-
 
| Paper
| [[2020Vilas_Monotomo]]
| Resolution determination in tomograms
|-
 
|}
 
=== Subtomogram analysis ===
 
{|
 
| Paper
| [[2000Bohm_Template]]
| Macromolecule finding by template matching
|-
 
| Paper
| [[2002Frangakis_Template]]
| Macromolecule finding by template matching
|-
 
| Paper
| [[2006Nickell_Review]]
| Review of macromolecule finding by template matching (Visual Proteomics)
|-
 
| Paper
| [[2007Best_Review]]
| Review of Localization of Protein Complexes by Pattern Recognition
|-
 
| Paper
| [[2007Forster_Review]]
| Review of structure determination by subtomogram averaging
|-
 
| Paper
| [[2008Forster_Classification]]
| Classification of subtomograms using constrained correlation
|-
 
| Paper
| [[2008Bartesaghi_Classification]]
| Classification and averaging of subtomograms
|-
 
| Paper
| [[2008Schmid_Averaging]]
| Alignment and averaging of subtomograms
|-
 
| Paper
| [[2010Amat_Averaging]]
| Alignment and averaging of subtomograms exploiting thresholding in Fourier space
|-
 
| Paper
| [[2010Yu_PPCA]]
| Probabilistic PCA for volume classification
|-
 
| Paper
| [[2013Chen_Averaging]]
| Fast alignment of subtomograms using spherical harmonics
|-
 
| Paper
| [[2013Kuybeda_Averaging]]
| Alignment and averaging of subtomograms using the nuclear norm of the cluster
|-
 
| Paper
| [[2013Shatsky_Averaging]]
| Alignment and averaging of subtomograms with constrained cross-correlation
|-
 
| Paper
| [[2013Yu_Projection]]
| Subtomogram averaging by aligning their projections
|-
 
| Paper
| [[2014Chen_Autofocus]]
| Subtomogram averaging and classification with special attention to differences
|-
 
| Paper
| [[2014Yu_ReferenceBias]]
| Scoring the reference bias
|-
 
| Paper
| [[2014Voortman_LimitingFactors]]
| Limiting factors of subtomogram averaging
|-
 
| Paper
| [[2015Bharat_CTFCorrectedSubtomogramAveraging]]
| Subtomogram averaging with CTF correction using a Bayesian prior
|-
 
| Paper
| [[2015Yu_ReferenceBias]]
| Scoring the reference bias
|-
 
| Paper
| [[2016Bharat_Relion]]
| Subtomogram averaging with Relion
|-
 
| Paper
| [[2016Song_MatrixNorm]]
| Matrix norm minimization for tomographic reconstruction and alignment
|-
 
| Paper
| [[2017Castano_ParticlePicking]]
| Particle picking in tomograms for subtomogram averaging
|-
 
| Paper
| [[2017Frazier_Tomominer]]
| TomoMiner a software platform for large-scale subtomogram analysis
|-
 
| Paper
| [[2018Himes_emClarity]]
| emClarity for subtomogram averaging
|-
 
| Paper
| [[2018Zhao_Fast]]
| Fast alignment and maximum likelihod for subtomogram averaging
|-
 
| Paper
| [[2019Fokine_Enhancement]]
| Subtomogram enhancement through the locked self-rotation
|-
 
| Paper
| [[2019Han_Constrained]]
| Constrained reconstruction to enhance resolution
|-
 
| Paper
| [[2020Basanta_workflow]]
| Workflow for subtomogram averaging
|-
 
| Paper
| [[2020Zeng_GumNet]]
| GumNet: Subtomogram averaging using deep learning
|-
 
| Paper
| [[2021Cheng_Native]]
| 3D reconstruction only with 0-tilt images
|-
 
| Paper
| [[2021Du_Active]]
| Active learning to reduce the need of annotated samples
|-
 
| Paper
| [[2021Harastani_HEMNMA3D]]
| HEMNMA-3D: Continuous flexibility analysis of subtomograms using normal modes
|-
 
| Paper
| [[2021Lucas_Cistem]]
| Identification of particles in tomograms using Cistem
|-
 
| Paper
| [[2021Moebel_DeepFinder]]
| DeepFinder: Identification of particles in tomograms using neural networks
|-
 
| Paper
| [[2021Scaramuzza_Dynamo]]
| Subtomogram averaging workflow using Dynamo
|-
 
| Paper
| [[2021Singla_Measures]]
| Analysis of different measures to analyze subtomogram clusters
|-
 
| Paper
| [[2021Tegunov_M]]
| Image processing workflow for tilt-series (introduction of M)
|-
 
| Conference
| [[2021Zeng_OpenSet]]
| Unsupervised open set classification using deep learning
|-
 
| Paper
| [[2022Bandyopadhyay_Adaptation]]
| Cryo-Shift: a neural network to bridge the gap between simulated and experimental data
|-
 
| Paper
| [[2022Boehning_CompressedSensing]]
| Compressed sensing for subtomogram averaging
|-
 
| Paper
| [[2022Hao_Picking]]
| Detection of molecules in tomograms
|-
 
| Paper
| [[2022Harastani_TomoFlow]]
| TomoFlow: Continuous flexibility analysis of subtomograms using 3D dense optical flow
|-
 
| Paper
| [[2022Metskas_STA]]
| Tricks for a better Subtomogram Averaging
|-
 
| Paper
| [[2022Moebel_unsupervised]]
| Unsupervised classification of subtomograms using neural networks
|-
 
| Paper
| [[2022Peters_Feature]]
| Feature guided, focused 3D signal permutation for STA
|-
 
| Paper
| [[2023Balyschew_TomoBEAR]]
| TomoBEAR: tilt series alignment, reconstruction and subtomogram averaging
|-
 
| Paper
| [[2023Chaillet_Extensive]]
| Extensive angular sampling for picking in tomograms
|-
 
| Paper
| [[2023Cheng_GisSPA]]
| Detection of protein targets in 0-tilt images
|-
 
| Paper
| [[2023Genthe_PickYolo]]
| Subtomogram picking in tomograms
|-
 
| Paper
| [[2023Rice_TomoTwin]]
| Subtomogram picking in tomograms
|-
 
| Paper
| [[2024Almira_TTM]]
| Theory of the Tensor Template matching for cryoET
|-
 
| Paper
| [[2024Cruz_Template]]
| Template matching for cryoET
|-
 
| Paper
| [[2024Huang_MiLoPYP]]
| Self-supervised particle localization in tomograms
|-
 
| Paper
| [[2024Jin_Size]]
| Subtomogram picking based on size
|-
 
| Paper
| [[2024Karimi_Vesicle]]
| Picking of particles embedded in vesicles
|-
 
| Paper
| [[2024Liu_DeepETPicker]]
| DeepETPicker, subtomogram picker using deep learning
|-
 
| Paper
| [[2024Powell_TomoDRGN]]
| TomoDRGN: continuous heterogeneity in subtomograms
|-
 
| Paper
| [[2024Rangan_CryoDRGNET]]
| CryoDRGN-ET: heterogeneity analysis for subtomograms
|-
 
| Paper
| [[2024Wan_StopGap]]
| StopGap: program to locate, align and classify subtomograms
|-
 
| Paper
| [[2024Wang_TomoNet]]
| Subtomogram picking in flexible lattices
|-
 
| Paper
| [[2025Chaillet_PytomMatchPick]]
| pytom-match-pick: particle picking in tomograms
|-
 
| Paper
| [[2025Shah_TomoCPT]]
| TomoCPT: particle picking in tomograms
|-
 
| Paper
| [[2025Yan_MPicker]]
| Membrane protein picking in electron tomograms
|-
 
| Paper
| [[2025Bartesaghi_StrategiesHet3D]]
| Strategies for studying discrete heterogeneity
|-
 
|}
 
=== Single particle tomography ===
 
{|
 
| Paper
| [[2012Bartesaghi_Constrained]]
| 3D reconstruction by imposing geometrical constraints
|-
 
| Paper
| [[2012Zhang_IPET_FETR]]
| FETR: a focused reconstruction algorithm for a single molecule 3D structure determination without any averaging
|-
 
| Paper
| [[2015Galaz_SingleParticleTomography]]
| Set of tools for Single Particle Tomography in EMAN2
|-
 
| Paper
| [[2016Galaz_SingleParticleTomography]]
| Alignment algorithms and CTF correction
|-
 
|}
 
=== Missing-wedge correction ===
 
{|
 
| Paper
| [[2020Kovacs_Filaments]]
| Removal of missing wedge artifacts in filamentous tomograms
|-
 
| Paper
| [[2020Moebel_MCMC]]
| Missing wedge correction with Monte Carlo Markov Chains
|-
 
| Paper
| [[2020Zhai_LoTTor]]
| Missing-wedge correction by LoTTor ('''Lo'''w-'''T'''ilt '''T'''omographic 3D '''R'''econstruction for a single molecule structure)
|-
 
| Paper
| [[2023Zhang_REST]]
| Missing-wedge correction with neural networks
|-
 
| Paper
| [[2025Kiewisz_ProjectionSynthesis]]
| Projection synthesis of electron tomography data using neural networks
|-
 
|}
 
=== Molecular 3D dynamics  ===
 
{|
 
| Paper
| [[2015Zhang_IPET]]
| 3D Structural Dynamics of Macromolecules by individual-particle structures without averaging
|-
 
| Paper
| [[2023Vuillemot_MDTOMO]]
| 3D Structural Dynamics of using molecular dynamics and normal modes
|-
 
|}
 
=== Books and reviews ===
 
{|
 
| Paper
| [[2000Baumeister_Review]]
| Review of electron tomography
|-
 
| Paper
| [[2003Koster_Review]]
| Review of electron tomography
|-
 
| Paper
| [[2003Sali_Review]]
| Review of electron tomography
|-
 
| Paper
| [[2004Henderson_Review]]
| Review of electron microscopy
|-
 
| Paper
| [[2005Lucic_Review]]
| Review of electron tomography
|-
 
| Paper
| [[2006Fernandez_Review]]
| Review of electron microscopy
|-
 
| Book
| [[2006Frank_TomoBook]]
| Electron Tomography
|-
 
| Book
| [[2007McIntosh_Book]]
| Cellular Electron Microscopy
|-
 
| Paper
| [[2007Sorzano_Review]]
| Review of the image processing steps
|-
 
| Paper
| [[2008Fanelli_ImageFormation]]
| Review on the image formation model from the electron waves and open inverse-problems
|-
 
| Paper
| [[2008Fernandez_HPCReview]]
| High performance computing in electron cryomicroscopy
|-
 
| Paper
| [[2008Jonic_Review]]
| Comparison between electron tomography and single particles
|-
 
| Paper
| [[2012Kudryashev_Review]]
| Review of subtomogram averaging
|-
 
| Paper
| [[2013Briggs_Review]]
| Review of subtomogram averaging
|-
 
| Paper
| [[2016Beck_Review]]
| Review of molecular sociology
|-
 
| Paper
| [[2016Ercius_Review]]
| Electron tomography for hard and soft materials research
|-
 
| Paper
| [[2017Galaz_Review]]
| Review of single particle tomography
|-
 
| Paper
| [[2017Plitzko_Review]]
| Review of electron tomography, FRET and FIB milling
|-
 
| Paper
| [[2019Schur_Review]]
| Review of electron tomography and subtomogram averaging
|-
 
| Paper
| [[2021Frangakis_Review]]
| Review of tomogram denoising in electron tomography
|-
 
| Paper
| [[2022Forster_Review]]
| Review of subtomogram averaging
|-
 
| Paper
| [[2022Liedtke_Review]]
| Review of electron tomography in bacterial cell biology
|-
 
| Paper
| [[2022Liu_Review]]
| Review of beam image shift and subtomogram averaging
|-
 
| Paper
| [[2023Kim_Review]]
| Review of particle picking and volume segmentation
|-
 
| Paper
| [[2023Ochner_Review]]
| Review of electron tomography as a way to visualize macromolecules in their native environment
|-
 
| Paper
| [[2023Zhao_Review]]
| Review of computational methods for electron tomography
|-
 
| Paper
| [[2023Watson_Review]]
| Review of computational methods for electron tomography
|-
 
| Paper
| [[2024Hutchings_Review]]
| Review of in situ electron tomography
|-
 
| Paper
| [[2024Schiotz_Review]]
| Review of in situ electron tomography
|-
 
| Paper
| [[2025Martinez_Review]]
| Review of template matching in electron tomography
|-
 
| Paper
| [[2025Wan_Review]]
| Review of sample preparation and data analysis for electron tomography
|-
 
|}
 
=== Software ===
 
{|
 
| Paper
| [[1996Kremer_IMOD]]
| IMOD
|-
 
| Paper
| [[1996Chen_Priism/IVE]]
| Priism/IVE
|-
 
| Paper
| [[1996Frank_Spider]]
| Spider
|-
 
| Paper
| [[2004Sorzano_Xmipp]]
| Xmipp
|-
 
| Paper
| [[2005Nickell_TOM]]
| TOM Toolbox
|-
 
| Paper
| [[2007Messaoudi_TomoJ]]
| TomoJ
|-
 
| Paper
| [[2008Heymann_BsoftTomo]]
| Bsoft
|-
 
| Paper
| [[2012Zhang IPET FETR]]
| IPET
|-
 
| Paper
| [[2015Ding_CaltechTomography]]
| Caltech tomography database
|-
 
| Paper
| [[2015Noble_AppionProtomo]]
| Batch fiducial-less tilt-series alignment in Appion using Protomo
|-
 
| Paper
| [[2015vanAarle_Astra]]
| ASTRA Toolbox
|-
 
| Paper
| [[2016Liu_FullMechTomo]]
| Fully mechanically controlled automated electron microscopic tomography
|-
 
| Paper
| [[2017Han_AuTom]]
| Software platform for Electron Tomography
|-
 
| Paper
| [[2017Wan_Simulator]]
| Electron Tomography Simulator
|-
 
| Paper
| [[2020Martinez-Sanchez_PySeg]]
| Template-free membrane proteins detection
|-
 
| Paper
| [[2021Burt_RWD]]
| Interoperability between Relion, Warp M, and Dynamo
|-
 
| Paper
| [[2022Jimenez_ScipionTomo]]
| Electron tomography within Scipion
|-
 
 
| Paper
| [[2022Martinez_PyOrg]]
| Point pattern analysis for coordinates in tomograms
|-
 
| Paper
| [[2022Ni_EmClarity]]
| Processing protocols with EmClarity
|-
 
| Paper
| [[2022Rodriguez_Mepsi]]
| Simulation of tomograms with membrane-embedded proteins
|-
 
| Paper
| [[2023Liu_NextPYP]]
| NextPYP: a software platform for cryoET
|-
 
| Paper
| [[2023Yee_Ot2Rec]]
| Ot2Rec: a software workflow for cryoET
|-
 
| Paper
| [[2024Burt_Relion5]]
| Subtomogram Analysis with RELION 5
|-
 
| Paper
| [[2024Comet_TomoLive]]
| TomoLive: Application for cryoET processing in streaming
|-
 
| Paper
| [[2024Gaifas_Blik]]
| Blik: Application for cryoET annotation and analysis
|-
 
| Paper
| [[2024Horstmann_PATo]]
| PATo: web application for cryoET processing in streaming
|-
 
| Paper
| [[2024Maurer_PyTME]]
| PyTME: Template matching for cryoET
|-
 
| Paper
| [[2024Martinez-Sanchez_PolNet]]
| PolNet: Simulating the Cellular Context
|-
 
| Paper
| [[2025Harar_FakET]]
| FakET: Simulation of electron tomography data using style transfer
|-
 
| Paper
| [[2025Zhan_AITom]]
| AITom: AI-guided CryoET Analysis Toolkit
|-
 
|}
 
== 2D Crystals ==
 
=== 2D Preprocessing ===
 
{|
 
| Paper
| [[1982Saxton_Averaging]]
| Radial Correlation Function
|-
 
| Paper
| [[1984Saxton_Distortions]]
| 3D Reconstruction of distorted crystals
|-
 
| Paper
| [[1986Henderson_Processing]]
| General 2D processing
|-
 
| Paper
| [[2000He_PhaseAlignment]]
| Phase consistency and Alignment
|-
 
| Paper
| [[2006Gil_Unbending]]
| Crystal unbending
|-
 
|}
 
=== Classification ===
{|
 
| Paper
| [[1988Frank_Classification]]
| MSA and classification in electron crystallography
|-
 
| Paper
| [[1996Fernandez_SOM]]
| Classification based on self organizing maps
|-
 
| Paper
| [[1998Sherman_MSA]]
| Classification based on MSA
|-
 
|}
=== 3D Reconstruction ===
 
{|
 
| Paper
| [[1985Wang_Solvent]]
| Solvent flattening
|-
 
| Paper
| [[1990Henderson_Processing]]
| General 3D processing
|-
 
| Paper
| [[2004Marabini_ART]]
| Algebraic Reconstruction Technique with blobs for crystals (Xmipp)
|-
 
| Paper
| [[2018Biyani_Badlu]]
| Image processing for badly ordered crystals
|-
 
|}
 
=== Books and reviews ===
 
{|
 
| Paper
| [[1998Walz_Review]]
| Review of 2D crystallography
|-
 
| Paper
| [[1999Glaeser_Review]]
| Review of 2D crystallography
|-
 
| Paper
| [[2001Ellis_Review]]
| Review of 2D crystallography
|-
 
| Paper
| [[2001Glaeser_Review]]
| Review of 2D crystallography
|-
 
| Paper
| [[2004Henderson_Review]]
| Review of electron microscopy
|-
 
| Paper
| [[2006Fernandez_Review]]
| Review of single particles, electron tomography and crystallography
|-
 
| Paper
| [[2007Sorzano_Review]]
| Review of the image processing steps
|-
 
|}
 
=== Software ===
 
{|
 
| Paper
| [[1996Crowther_MRC]]
| MRC
|-
 
| Paper
| [[2004Sorzano_Xmipp]]
| Xmipp
|-
 
| Paper
| [[2007Gipson_2dx]]
| 2dx
|-
 
| Paper
| [[2007Heymann_Bsoft]]
| Bsoft
|-
 
| Paper
| [[2007Philippsen_IPLT]]
| IPLT
|-
 
|}
 
== 3D Crystals - MicroED ==
 
=== Sample Preparation ===
{|
| Paper
| [[2016Shi_Preparation]]
| Sample Preparation
|-
 
| Paper
| [[2024Gillman_Cone]]
| Eliminating the missing cone
 
|}
 
=== Data Collection ===
{|
| Paper
| [[2014Nannenga_CR]]
| Continuous rotation
 
|}
=== Data Processing ===
{|
 
| Paper
| [[2011Wisedchaisri_PhaseExtension]]
| Fragment-based phase extension
|-
 
| Paper
| [[2015Hattne_Processing]]
| Data Processing
|-
| Paper
| [[2016Hattne_Correction]]
| Image correction
|}
 
=== Software ===
{|
 
| Paper
| [[2014Iadanza_Processing]]
| Data Processing of still diffraction data
|}
 
=== Books and Reviews ===
{|
|  Paper
| [[2014Nannenga_Review ]]
| Review of MicroED
|-
 
| Paper
| [[2016Liu_Review ]]
| Review of MicroED
|-
 
| Paper
| [[2016Rodriguez_Review ]]
| Review of MicroED
|-
 
|}
 
== Helical particles ==
 
=== Filament picking ===
 
{|
 
| Paper
| [[2021Thurber_Automated]]
| Automated picking of filaments
|-
 
| Paper
| [[2023Li_Classification]]
| Classification of filament segments using language models
|-
 
| Paper
| [[2025Peng_DiamTR]]
| DiamTR: Classification of filaments by diameter
|-
 
|}
 
=== Filament corrections ===
 
{|
 
| Paper
| [[1986Egelman_Curved]]
| Algorithm for correcting curved filaments
|-
 
| Paper
| [[1988Bluemke_Pitch]]
| Algorithm for correcting filaments with different helical pitches
|-
 
| Paper
| [[2006Wang_Pitch]]
| Algorithm for correcting filaments with different helical pitches
|-
 
| Paper
| [[2016Yang_Flexible]]
| Algorithm for correcting filaments with flexible subunits
|-
 
| Paper
| [[2019Ohashi_SoftBody]]
| Algorithm for correcting filaments with flexible helices
|-
 
|}
 
=== Reconstruction ===
 
{|
 
| Paper
| [[1952Cochran_Fourier]]
| Fourier Bessel transform of filamentous structures
|-
 
| Paper
| [[1958Klug_Fourier]]
| Fourier Bessel decomposition of the projection images
|-
 
| Paper
| [[1970DeRosier_Rec]]
| Image processing steps towards 3D reconstruction
|-
 
| Paper
| [[1988Stewart_Rec]]
| Image processing steps towards 3D reconstruction
|-
 
| Paper
| [[1992Morgan_Rec]]
| Image processing steps towards 3D reconstruction
|-
 
| Paper
| [[2005Wang_Iterative]]
| Iterative Fourier-Bessel algorithm
|-
 
| Paper
| [[2007Egelman_Iterative]]
| Iterative real-space algorithm
|-
 
| Paper
| [[2010Egelman_Pitfalls]]
| Pitfalls in helical reconstruction
|-
 
| Paper
| [[2013Desfosses_Spring]]
| Helical processing with Spring
|-
 
| Paper
| [[2015Zhang_seam]]
| Workflow for the detection of the lattice seam
|-
 
| Paper
| [[2016Rohou_Frealix]]
| Helical processing with Frealix
|-
 
| Paper
| [[2017_He]]
| Helical processing with Relion
|-
 
| Paper
| [[2019_Pothula]]
| 3D Classification through 2D analysis
|-
 
| Paper
| [[2025_Huang]]
| Helical parameter estimation by cylinder unrolling
|-
 
| Paper
| [[2025Li_Helicon]]
| Helicon: Helical parameter determination and 3D reconstruction from one image
|-
 
|}
 
=== Validation ===
 
{|
 
| Paper
| [[2014Egelman_ambiguity]]
| How to detect incorrect models
|-
 
| Paper
| [[2025Li_validation]]
| Validation of the helical symmetry parameters in EMDB
|-
 
|}
 
=== Books and reviews ===
 
{|
 
| Paper
| [[1970DeRosier_Rec]]
| Image processing steps towards 3D reconstruction
|-
 
| Paper
| [[1992Morgan_Rec]]
| Image processing steps towards 3D reconstruction
|-
 
| Paper
| [[2004Henderson_Review]]
| Review of electron microscopy
|-
 
| Paper
| [[2015Sachse_Review]]
| Review of the image processing steps in helical particles
|-
 
| Paper
| [[2021Egelman_Review]]
| Review of reconstruction problems in helical structures
|-
 
| Paper
| [[2022Wang_Review]]
| Review of reconstruction problems in helical structures
|-
 
| Paper
| [[2022Kreutzberger_Review]]
| Review of helical reconstruction
|-
 
|}
 
=== Software ===
 
{|
 
| Paper
| [[1996Carragher_Phoelix]]
| Phoelix
|-
 
| Paper
| [[1996Crowther_MRC]]
| MRC
|-
 
| Paper
| [[1996Owen_Brandeis]]
| Brandeis
|-
 
|}
 
== Icosahedral particles ==
 
=== Reconstruction ===
 
{|
 
| Paper
| [[1970Crowther_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-
 
| Paper
| [[1971Crowther_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-
 
| Paper
| [[1996Fuller_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-
 
| Paper
| [[1997Thuman_Rec]]
| Reconstruction of icosahedral viruses in Fourier space
|-
 
| Paper
| [[2019Goetschius_Asymmetric]]
| Approaches to reconstruct asymmetric features in viruses
|-
 
| Paper
| [[2025Chen_Asymmetric]]
| Approaches to reconstruct asymmetric features in viruses
|-
 
|}
 
=== Classification ===
 
{|
 
| Paper
| [[2005Scheres_Virus]]
| Classification of virus capsids in real space
|-
 
|}
 
=== Books and reviews ===
 
{|
 
| Paper
| [[1999Baker_Review]]
| Review of reconstruction of icosahedral viruses
|-
 
| Paper
| [[1999Conway_Review]]
| Review of reconstruction of icosahedral viruses
|-
 
| Paper
| [[2000Thuman_Review]]
| Review of reconstruction of icosahedral viruses
|-
 
| Paper
| [[2003Lee_Review]]
| Review of reconstruction of icosahedral viruses
|-
 
| Paper
| [[2003Navaza_Review]]
| Review of reconstruction of icosahedral viruses
|-
 
| Paper
| [[2006Grunewald_Review]]
| Review of reconstruction of icosahedral viruses
|-
 
|}
 
=== Software ===
 
{|
 
| Paper
| [[1996Baker_EMPFT]]
| EMPFT
|-
 
| Paper
| [[1996Crowther_MRC]]
| MRC
|-
 
| Paper
| [[1996Frank_Spider]]
| Spider
|-
 
| Paper
| [[1996VanHeel_Imagic]]
| Imagic
|-
 
| Paper
| [[2004Sorzano_Xmipp]]
| Xmipp
|-
 
| Paper
| [[2013DeLaRosa_Xmipp30]]
| Xmipp 3.0
|-
 
| Paper
| [[2013Morin_Sliz SBGrid]]
| SBGrid presentation for eLife
|-
 
|}
 
== Single molecule 3D structure (non-averaged) ==
 
=== Variety analysis methods ===
 
{|
 
| Paper
| [[2024Liu_RNA]]
| Variety of RNA tertiary structures
|-
 
| Paper
| [[2024Zhang_Nucleosome]]
| Dynamics of nucleosome arrays
|-
 
| Paper
| [[2022Zhang_NucleosomeTrasition]]
| Aggregation of nucleosome arrays during phase transition
|-
 
| Paper
| [[2018Lei_DNABennet]]
| Flexibility of DNA origami Bennett linkages
|-
 
| Paper
| [[2016Zhang_DNANG]]
| Flexibility of DNA-nanogold complex
|-
 
| Paper
| [[2015Zhang_IgG1]]
| Dynamics of IgG1 antibodies
|-
 
|}
 
=== Process methods ===
 
{|
 
| Paper
| [[2012Zhang_IPET]]
| Forcused electron tomography reconstration (FETR) method
|-
 
| Paper
| [[2016Liu_AutoET]]
| Fully Mechanically Controlled Automated Electron Microscopic Tomography
|-
 
| Paper
| [[2018Wu_Contrast]]
| An Algorithm for Enhancing the Image Contrast of Electron Tomography
|-
 
| Paper
| [[2020Zhai_LoTToR]]
| Missing-wedge correction for the low-tilt tomographic 3D reconstruction of a single molecule
|-
 
|}
 
=== Reviews ===
 
{|
 
| Paper
| [[2022Han_Radiation]]
| Cryo-ET related radiation-damage parameters for single molecule 3D structure determination
|-
 
|}
 
== Liquid-cell TEM / in-situ TEM ==
 
{|


| Paper
| Paper
| [[2020Ren_LTEM]]
| [[2020Ren_LTEM]]
| Real-time dynamic imaging of sample in liquid phase
| Real-time dynamic imaging of sample in liquid phase
|-
 
| Paper
| [[2023Kong_ViralEntry]]
| Molecular imaging of protein, virus and cell samples at room temperature
|-
 
 
|}
 
== Databases ==
 
{|
 
| Paper
| [[2003Boutselakis_EMSD]]
| EMSD database
|-
 
| Paper
| [[2005Heymann_Conventions]]
| Conventions for software interoperability
|-
 
| Paper
| [[2005Heymann_Conventions]]
| Conventions for software interoperability
|-
 
| Paper
| [[2011Kim_CDDB]]
| Conformational Dynamics Data Bank
|-
 
| Paper
| [[2011Lawson_EMDB]]
| Electron Microscopy Data Bank
|-
 
| Paper
| [[2013Ison_EDAM]]
| EDAM, an ontology of bioinformatics operations
|-
 
| Paper
| [[2016Iudin_EMPIAR]]
| EMPIAR raw data database
|-
 
| Paper
| [[2016Patwhardan_EMDB]]
| EMDB, PDB, ...
|-
 
| Paper
| [[2017Gore_Validation]]
| Validations of PDB submissions
|-
 
| Paper
| [[2017Patwhardan_Trends]]
| Trends at EMDB
|-
 
| Paper
| [[2017Shao_PDBQuality]]
| Quality metrics in PDB
|-
 
| Paper
| [[2018Tawari_search]]
| Search of 3D structures in a database using 2D experimental images
|-
 
| Paper
| [[2018wwwPDB_PDB]]
| Review of PDB advances
|-  
|-  
|}
== Databases ==
{|


| Paper
| Paper
| [[2003Boutselakis_EMSD]]
| [[2021Nair_PDBe]]
| EMSD database
| PDBe API
|-
 
| Paper
| [[2005Heymann_Conventions]]
| Conventions for software interoperability
|-  
|-  


| Paper
| Paper
| [[2005Heymann_Conventions]]
| [[2022Wang_EMDB]]
| Conventions for software interoperability
| Validation analysis of EMDB entries
|-  
|-  


| Paper
| Paper
| [[2011Kim_CDDB]]
| [[2022Westbrook_mmCIF]]
| Conformational Dynamics Data Bank
| PDBx/mmCIF ecosystem
|-  
|-  


| Paper
| Paper
| [[2011Lawson_EMDB]]
| [[2024Kleywegt_ArchivingValidation]]
| Electron Microscopy Data Bank
| Community recommendations for archival and validation
|-  
|-  


| Paper
| Paper
| [[2013Ison_EDAM]]
| [[2024Ermel_DataPortal]]
| EDAM, an ontology of bioinformatics operations
| CryoET Data Portal
|-  
|-  


| Paper
| Paper
| [[2016Iudin_EMPIAR]]
| [[2024Vallat_IHMCIF]]
| EMPIAR raw data database
| IHMCIF extension of mmCIF for integrative modelling
|-  
|-  


| Paper
| Paper
| [[2016Patwhardan_EMDB]]
| [[2024wwPDB_EMDB]]
| EMDB, PDB, ...
| Review of EMDB
|-
 
| Paper
| [[2017Gore_Validation]]
| Validations of PDB submissions
|-
 
| Paper
| [[2017Patwhardan_Trends]]
| Trends at EMDB
|-
 
| Paper
| [[2017Shao_PDBQuality]]
| Quality metrics in PDB
|-
 
| Paper
| [[2018Tawari_search]]
| Search of 3D structures in a database using 2D experimental images
|-
 
| Paper
| [[2018wwwPDB_PDB]]
| Review of PDB advances
|-  
|-  



Latest revision as of 10:16, 9 January 2026

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Electron microscopy images

Useful resources

Map of cryoEM microscopes and labs in the world

CryoEM genealogy

Online courses and Learning material

Caltech (same course in Coursera) (latest version of the course in EM-learning)

MRC

MRC training channel

CNB-CSIC

Workshop on Computational methods for CryoEM

Workshop on Management of large CryoEM facilities

Icknield Course on Model Building and Refinement for High Resolution EM Maps

Tutorial on how to prepare negative staining samples

Tutorial on how to prepare samples

Do's and don'ts on sample preparation

NRAMM Workshop 2017 (course slides)

SBGrid videos about the programs they offer

Madrid course on single particle analysis

CCP-EM Spring symposium 2019

CCP-EM Spring symposium 2020

NCCAT Single Particle short course 2020

Cell atlas book by Grant Jensen and Catherine Oikonomou

Purdue CryoEM Virtual Reality Augmented Training

NCCAT Short course on Tomography

Map with CryoEM Facilities

NCCAT Single Particle Analysis short course

Algorithms for Structural Bioinformatics, AlgoSB2023, Cargese

One world CryoEM technical talks

Cryo-EMAcademy YouTube

In Situ CryoET eBic

Image formation

Paper 1971Erickson_CTF CTF model
Paper 1971Glaeser_Damage Radiation damage
Chapter 1971Hanszen_CTF Image formation model
Paper 1971Thon_Model CTF model
Paper 1974Taylor_Diffraction Electron diffraction of crystals
Paper 1975Unwin_Imaging Radiation dose
Paper 1977Wade_Model CTF model
Paper 1978Wade_Model CTF model
Paper 1979Hayward_Radiation Radiation damage
Paper 1984Cohen_Validity Validity of the CTF model at high frequencies
Paper 1988Toyoshima_Model Amplitud constrast
Paper 1992Wade_Model CTF model
Paper 1993Toyoshima_Model Amplitud constrast
Paper 2002DeCarlo_Damage Radiation damage in cryonegative staining
Paper 2004Egerton_Damage Radiation damage
Paper 2004Sorzano_Normalization Background noise is Gaussian
Paper 2008Downing_Twin Theoretical analysis of the CTF correction algorithms
Paper 2008Fanelli_ImageFormation Review on the image formation model from the electron waves and open inverse-problems
Paper 2009Baxter_NoiseCharacterization Characterization of the different noise sources in cryo-EM
Book 2009Rose_Optics Geometrical Charged-Particle Optics
Paper 2010Baker_Damage Radiation damage dependence on resolution
Paper 2010Bammes_Damage Radiation damage dependence on temperature
Paper 2010Gomez_Multislice Simulation of the multi slice model
Paper 2010Zewail_FourDimensional Review on the use of ultrafast EM
Paper 2011Bammes_CCD Performance of CCD cameras
Paper 2011Glaeser_Coma Image formation model including coma
Paper 2011Milazzo_DirectDetectors Evaluation of Direct Detectors
Paper 2011Rullgard_ImageSimulation Accurate simulation of EM images
Paper 2011Zhang LimitingFactors Limiting factor for atomic resolution in EM
Paper 2012Bammes_DirectDetection Performance of Direct detectors
Paper 2012Campbell_MotionCorrection Beam induced motion correction and direct detectors
Paper 2012Shang_HydrationLayer Simulation of PDB volumes explicitly considering the hydration layer
Paper 2013Egerton_RadiationDamage Review of TEM radiation damage and experimental ways of reducing it
Paper 2013Bai_ElectronCounting Electron counting and beam induced motion correction
Paper 2013Li_ElectronCounting Electron counting and beam induced motion correction
Paper 2013Shigematsu H_Noisemodels Noise models and cryo-EM drift correction with a direct-electron camera
Paper 2013Li X K2 noisemodels Influence of electron dose rate on electron counting images recorded with the K2 camera
Paper 2013Vulovic_CTFApproximations When to use the different approximations performed so that a projection with linear CTF is valid
Thesis 2013Vulovic_ImageFormation Ph.D. Thesis on the image formation in cryo-EM
Paper 2014Danev_PhasePlate Volta potential phase plate
Paper 2015Chiu_K2 Characterization of K2
Paper 2015Hawkes_AberrationCorrection Historical account of the development of lens corrections
Paper 2015Koeck_Quadratic Limitations of the linear approximation and use of the quadratic terms
Paper 2015Kuijper_FEI Description of the FEI Falcons
Paper 2015Lobato_MULTEM Simulation of multislice diffraction
Paper 2015McMullan_AmorphousIce Beam induced movement is caused by Brownian motion
Paper 2016Glaeser_Behaviour Behaviour of the specimen under the electron beam
Paper 2016Koeck_ADF Simulations of Annular Dark Field TEM
Paper 2017Fan_VPP 3D Reconstruction with under-focus and over-focus Volta Phase Plate micrographs
Paper 2017Koeck_ApertureDesign Aperture design for singe side band imaging
Paper 2017Mishyna_DNARadiation Review of radiation damage on DNA
Paper 2018Anoshina_Simulation Simulation of 2D and 3D EM images
Paper 2018Downing_DepthOfField Effects of the Depth of Field
Paper 2018DeJonge_SpatialResolution Theory of spatial resolution in liquid water or ice layers
Paper 2018Faruqi_DED Review of Direct Detectors
Paper 2018Hattne_RadiationDamage Analysis of radiation damage in EM
Paper 2018Hettler_Charging Charging of carbon thin films
Paper 2018Koeck_PhaseShift Design of a phase shift device
Paper 2018Noble_ParticleDistribution Particle distribution and ice thickness for Single Particles
Paper 2018Russo_ChargeAccumulation Charge accumulation in electron cryomicroscopy
Paper 2018Russo_SingleBandEM Ewald sphere correcion using single-side band image processing
Paper 2019Peet_EnergyDependence Energy dependence of radiation damage
Paper 2020Bromberg_Aberrations Estimation of strong high-order aberrations
Paper 2020Gruza_Atomic Detailed atomic models considering local charges and directional bonds
Paper 2020Naydenova_Buckling Beam induced movement explained as ice buckling
Paper 2020Zhang_LimitsSimulated Simulation of micrographs and 3D reconstruction for low weight proteins (14kDa)
Paper 2020Tichelaar_Thick Effect of sample thickness on the CTF
Paper 2020Yip_Atomic Atomic resolution by monochromator and a second-generation spherical aberration corrector
Paper 2020Zhang_LimitsSimulated Simulation of micrographs and 3D reconstruction for low weight proteins (14kDa)
Paper 2021Egerton_Inelastic PSF of inelastic scattering
Paper 2021Himes_Simulation Simulation of TEM images with special attention to inelastic scattering
Paper 2021Glaeser_Fading Defocus-dependent Thon-ring fading
Paper 2021Singer_Wilson Detailed analysis of Wilson statistics
Paper 2021Wieferig_Devitrification Devitrification reduces beam-induced movement in cryo-EM
Paper 2022Bharadwaj_Scattering Electron scattering properties and their use for map sharpening
Paper 2022Heymann_PSSNR Progressive Spectral Signal-to-Noise Ratio to assess quality and radiation damage
Paper 2022Dickerson_Inelastic The role of inelastic scattering in thick specimens
Paper 2022Kulik_TAAM Theoretical 3D electron diffraction electrostatic potential maps of proteins
Paper 2022Ravikumar_SideChains Comparison of side-chain dispersion in protein structures determined by cryo-EM and X-ray crystallography
Paper 2023Bromberg_Complex CTF and Ewald sphere correction using complex-valued images
Paper 2023Heymann_Ewald The Ewald sphere/focus gradient does not limit the resolution of cryoEM reconstructions
Paper 2023McMullan_100kV CryoEM at 100kV
Paper 2023Schreiber_charge Time dynamics of charge buildup
Paper 2023Shi_Compression Protein compression due to ice formation
Paper 2024Bochtler_Probes X-rays, electrons, and neutrons as probes of atomic matter
Paper 2024Dickerson_magnification Accurate determination of magnification using gold
Paper 2024Joosten_Roodmus Simulation of micrographs of heterogeneous macromolecules
Paper 2024Parkhurst_IceSimulation Projections of amorphous ice simulation simulated with Gaussian Random Fields
Paper 2024Remis_Damage Radiation damage revealed by phase plates
Paper 2025Dickerson_Damage Reduced radiation damage at liquid helium temperature
Paper 2025Wu_ZeroLossCCCorrected Imaging with chromatic aberration correction and zero loss electrons
Paper 2026Heymann_Ewald The relationship between the Ewald sphere and exit wave explored using focal series electron micrographs

Collection geometry

Chapter 1980Hoppe_Wedge Missing wedge
Paper 1987Radermacher_RCT Random Conical Tilt and Single axis tilt
Paper 1988Radermacher_RCT Random Conical Tilt and Single axis tilt
Paper 1995Penczek_Dual Dual axis tomography
Paper 1997Mastronarde_Dual Dual axis tomography
Paper 2003Ludtke_FocusPairs Focus pairs for single particles
Paper 2005Lanzavecchia_Conical Conical tomography
Paper 2005Zampighi_Conical Conical tomography
Paper 2006Leschziner_OT Orthogonal Tilt
Paper 2006Messaoudi_Multiple Multiple axis tomography
Paper 2012Kudryashev_FocusPairs Focus pairs tomography
Paper 2014Hovden_TiltFocus Combining tilt series with focus series
Paper 2015Sorzano_RandomConicalTilt General formulation of Random Conical Tilt
Paper 2017Hagen_DoseTomography Dose optimization for subtomogram averaging
Paper 2017Tan_PreferredViews Solving preferred views problems through tilting
Paper 2017Donati_Compressed Compressed sensing for STEM
Paper 2018Oveisi_Stereo Stereo-vision with EM
Paper 2018Cheng_BeamShift Fast image acquisition through beam-shift
Paper 2019Wu_BeamShiftAndTilt Fast image acquisition through beam-shift and beam tilt control
Paper 2023Seifer_RevisedSaxton Revised Saxton geometry for tilt series acquisition

Sample preparation

Paper 1982Dubochet_Sample Vitreous ice
Paper 1986Lepault_Sample Fast freezing
Paper 1995Dubochet_Sample High-pressure freezing
Paper 1995VanMarle_Sample Sample damages in resin
Paper 1998Adrian_Sample Cryo negative staining
Paper 2002DeCarlo_Damage Radiation damage in cryonegative staining
Paper 2002Hsieh_Sample Cryofixation
Paper 2004AlAmoudi_Sample CEMOVIS
Paper 2008Studer_Sample Review on high pressure freezing
Paper 2009Pierson_Sample Review on sample preparation for electron tomography
Paper 2010Zhang_OpNS Optimized negative staining (OpNS) for small protein and lipoprotein imaging
Paper 2012Zhang_Cryo-PS Cryo-positive staining (Cryo-PS)
Paper 2014Russo_GoldGrids Gold grids for single particles
Paper 2015Cabra_Sample Review on sample preparation for single particles with videos
Paper 2015Chari_ProteoPlex Fast evaluation of the structural stability
Paper 2016Passmore_Review Tutorial chapter on sample preparation
Paper 2016Razinkov_Vitrification New vitrification method
Paper 2016Takizawa_Sample Review on sample preparation for EM
Paper 2016Thompson_Sample Review on sample preparation for EM
Paper 2017Arnold_BlottingFree Blotting-free preparation
Paper 2017Earl_review Review of sample preparation
Paper 2017Feng_SprayingPlunging Spraying plunging
Paper 2017He_FIB Cryo FIB lamella for TEM
Paper 2017Peitsch_Sample iMEM: Isolation of Plasma Membrane for Cryoelectron Microscopy
Paper 2017Scapin_Storage Cryo storage of samples
Paper 2017Schaffer_FocusedIonBeam Focused Ion Beam sample preparation for membrane proteins
Paper 2017Scherr_HydrogelNanomembranes Sample preparation for membrane proteins
Paper 2018Anderson_CLEM Correlated light and EM
Paper 2018Arnold_Review Review on sample preparation with special emphasis on microfluidic approaches
Paper 2018Ashtiani_femtolitre Delivery of femtolitre droplets using surface acoustic wave based atomisation for cryo-EM grid preparation
Paper 2018Dandey_Spotiton Spotiton, a device for vitrification
Paper 2018Gewering_Detergents Detergent background in negative stain
Paper 2018Li_CLEM Correlated light and EM
Paper 2018Noble_Reducing Reducing particle adsorption
Paper 2018Palovcak_Graphene Preparation of graphene-oxide cryo-EM grids
Paper 2018Rice_Ice Routine determination of ice thickness
Paper 2018Schmidli_Miniaturized Protein isolation and sample preparation
Paper 2018Wei_Grids "Self-wicking" nanowire grids
Paper 2019DImprima_Denaturation Protein denaturation at the air-water interface and how to prevent it
Paper 2019Rubinstein_ultrasonic Ultrasonic specimen preparation device
Paper 2019Song_FalconIII Comparison of the modes of Falcon III
Paper 2020Cianfrocco_Wrong What could go wrong?
Paper 2020Egelman_Ice Problems with the ice
Paper 2020Fassler_Printing 3D printed cell culture grid holder
Paper 2020Klebl_Deposition Sample deposition onto CryoEM grids: sprays and jets
Paper 2020Maeots_TimeResolved Time resolved CryoEM by microfluidics
Paper 2020Tan_ThroughGrid Through-grid wicking enables high-speed 1 cryoEM specimen preparation
Paper 2020Yoder_TimeResolved Time resolved CryoEM by light estimulation
Paper 2020Zachs_FIB Automation for FIB milling
Paper 2021Bieber_FIBET Sample preparation for correlative FIB milling and CryoET
Paper 2021Budell_TimeResolved Time resolved CryoEM with Spotiton
Paper 2021Casasanta_Microchip Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy
Paper 2021Frechard_Preparation Optimization of Sample Preparation
Paper 2021Engstrom_Nitrogen Samples vitrified in boiling nitrogen
Paper 2021Jagota_GoldNanoparticles Gold nanoparticles to assess flexibility
Paper 2021Jiang_MoAu Holey Gold Films on Molybdenum Grids
Paper 2021Jonaid_Liquid Liquid phase EM
Paper 2021Ki_Conformational Conformational Distribution of a Small Protein with Nanoparticle-Aided CryoEM
Paper 2021Li_detergents The effect of detergents on preferential orientations
Paper 2021Voss_Melting Rapid melting and revitrification as an approach to microsecond time-resolved cryoEM
Paper 2021Zhang_Pegylation Improving particle quality in cryo-EM by PEGylation
Paper 2022Chen_Detergents Role of detergents in the air-water interface
Paper 2022Levitz_Chameleon Effects of dispense-to-plunge speed on particle concentration, complex formation, and final resolution
Paper 2022Naydenova_Grid Integrated wafer-scale manufacturing of electron cryomicroscopy specimen supports
Paper 2022Russo_Review Review of sample preparation issues
Paper 2022Scher_FIB Sample preparation for FIB-SEM and Correlative microscopy
Paper 2023Basanta_Graphene Fabrication of Monolayer Graphene-Coated Grids
Paper 2023Grassetti_Graphene Improving graphane monolayer sample preparation
Paper 2023Han_Sample Challenges in making ideal cryo-EM samples
Paper 2023Liu_AirWater Review on sample preparation techniques to deal with the air-water interface
Paper 2023Langeberg_RNAScaffold RNA scaffolds for small proteins
Paper 2023Neselu_IceThickness Effect of ice thickness on resolution
Paper 2023Torino_TimeResolved Device for the preparation of time-resolved CryoEM experiments
Paper 2023Venien_Membrane Review on the preparation of membrane proteins
Paper 2023Zheng_Ultraflat Uniform thin ice on ultraflat graphene grids
Paper 2024Esfahani_SPOTRASTR SPOT-RASTR: A sample preparation technique that overcomes preferred orientations
Paper 2024Abe_LEA LEA proteins to reduce the air-water interface interaction
Paper 2024Bhattacharjee_TimeResolved Time-resolved cryoEM with a microfluidic device
Paper 2024Harley_40 Pluge freezing over 40 degrees
Paper 2024Henderikx_Vitrojet Use cases of Vitrojet
Paper 2024Hsieh_MinIce Minimization of the ice contamination for cryoET
Paper 2024Liu_Graphene Review of the use of graphene for grid preparation
Paper 2024Mueller_Facility Sample workflow at the facility
Paper 2024Tuijtel_Lamellae Optimizing lamellae for subtomogram averaging
Paper 2024Yadav_Orientation Experimental factors affecting orientation distribution
Paper 2025Chen_Detergent Review on the use of detergents to extract membran proteins and their effects on CryoEM
Paper 2025Elad_Review Review of sample preparation for in situ protein visualization
Paper 2025Grant_Nanodisc Review on the use of nanodiscs for sample preparation
Paper 2025Gusach_Diffusion Sample vitrification faster than protein diffusion
Paper 2025Haynes_OptimalIce Vitrification conditions for optimal ice thickness
Paper 2025Sun_PlasmaMembranes Sample preparation pipeline for plasma membrane analysis by CryoET

Automated data collection

Paper 1992Dierksen_Automatic Automated data collection
Paper 1992Koster_Automatic Automated data collection
Paper 1996Fung_Automatic Automated data collection for tomography
Paper 2001Zhang_Automatic Automated data collection: AutoEM
Paper 2003Ziese_Automatic Automated autofocusing
Paper 2004Potter_Automatic Automated sample loading
Paper 2004Zheng_Automatic Automated data collection
Paper 2005Lei_Automatic Automated data collection: AutoEM
Paper 2005Suloway_Automatic Automated data collection: Leginon
Paper 2007Yoshioka_RCT Automated Random Conical Tilt
Paper 2011Korinek_TOM2 Automated acquisition with TOM2
Paper 2015Li_UCSFImage Automated acquisition with UCSFImage
Paper 2016Gil_Fuzzy Real time decisions during acquisition with neuro-fuzzy method
Paper 2016Liu_TiltControl Accurate control of the tilt angle for electron tomography
Paper 2016Vargas_FoilHole Determination of image quality at low magnification
Paper 2017Alewijnse_Best Best practices for managing large CryoEM facilities
Paper 2017Biyani_Focus Automatic processing of micrographs
Paper 2018Gomez_Facilities Use of Scipion at facilities
Paper 2018Sorzano_Gain Estimation of the DDD camera gain or residual gain
Paper 2019Chreifi_TiltSeries Rapid tilt-series acquisition for electron cryotomography
Paper 2019Eng_ImageCompression 3D Reconstruction from compressed images
Paper 2019Eisenstein_FISE Improved applicability and robustness of fast cryo-electron tomography data acquisition
Paper 2019Hamaguchi_CryoARM CryoARM data acquisition
Paper 2019Maluenda_Scipion Automated workflow processing for facilities
Paper 2019Schorb_ET Automated acquisition in Electron Tomography
Paper 2019Tegunov_Warp Automatic micrograph processing with Warp
Paper 2019Thompson_Protocol Protocol for EM acquisition
Paper 2020Baxa_Facility Operational workflow in a facility
Paper 2020Guo_EER Electron event representation for acquisition
Paper 2020Li_Workflow Workflow for automatic reconstruction
Paper 2020Maruthi_Automatic Evaluation of MicAssess and CryoAssess
Paper 2020Sader_Facility Microscope installation and operation in a facility
Paper 2020Schenk_CryoFlare CryoFlare, automatic data acquisition
Paper 2020Stabrin_Transphire TranSPHIRE: Automated and feedback-optimized on-the-fly processing for cryo-EM
Paper 2020Yokoyama_Good Deep learning for determining good regions in a grid
Paper 2020Weis_Acquisition Suggestions for high-quality and high-throughput acquisition
Paper 2021Feathers_Superresolution Effects of superresolution and magnification on final resolution
Paper 2021Bouvette_Bisect Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography
Paper 2021Chreifi_FISE Rapid tilt-series method for cryo-electron tomography: Characterizing stage behavior during FISE acquisition
Paper 2021Danev_Eval Evaluation of different automatic acquisition schemes
Paper 2021Efremov_ComaCorrected Coma-corrected rapid single-particle cryo-EM data collection on the CRYO ARM 300
Paper 2021Herzik_Setup Setup for parallel illumination
Paper 2021Kayama_Multipurpose Below 3 Å structure of apoferritin using a multipurpose TEM with a side entry cryoholder
Paper 2021Lane_NegativeBias Negative potential bias for faster imaging
Paper 2021Rheinberger_IceThickness Scripts to measure ice thickness
Paper 2021Yang_CRIM Computer readable image markers (CRIM) for correlative microscopy
Paper 2021Weis_Strategies Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition
Paper 2021Wypych_gP2S LIMS of microscope sessions
Paper 2021Yang_CLEM Automated correlative microscopy
Paper 2021Yonekura_Hole Automated hole detection using YOLO
Paper 2022Bepler_Smart Smart data collection
Paper 2022Bouvette_SmartScope SmartScope
Paper 2022Flutty_bits Bit-precision for SPA and ET
Paper 2022Hagen_Screening Screening of ice thickness using energy filter-based plasmon imaging
Paper 2022Hohle_Ice Screening of ice thickness using interferometry
Paper 2022Peck_200 High-speed high-resolution data collection on a 200 keV cryo-TEM
Paper 2022Peck_Montage Montage electron tomography
Paper 2022Zhu_ElectronCounting New algorithm for electron counting at the microscope
Paper 2023Cheng_Leginon Smart data collection with Leginon
Paper 2023Kim_Ptolemy Smart data collection with Ptolemy
Paper 2023Last_Ice Measuring the ice thickness with an optical device and a neural network
Paper 2023Mendez_Pipelines Evaluation of pipelines for stream processing
Paper 2024Bobe_Calibration CryoEM Calibration workflow
Paper 2024Eisenstein_SPACETomo Automated acquisition of tilt series
Conference 2024Fan_RL Reinforcement learning to optimize the microscope use
Paper 2024Hatton_EMinsight EMinsight: a tool to capture cryoEM microscope configuration and experimental outcomes for analysis and deposition
Paper 2024Xu_Miffi Miffi: automatic classification of micrographs
Paper 2025Bhandari_Fast Data acquisition in EPU Fast mode

Single particles

Automatic particle picking

Paper 1982VanHeel_Detection Detection of particles in micrographs
Paper 2001Nicholson_Review Review on automatic particle picking
Paper 2001Zhu_Filaments Automatic identification of filaments in micrographs
Paper 2004Sigworth_Detection Classical detection theory and the cryo-EM particle selection problem
Paper 2004Volkmann_ParticlePicking An approach to automated particle picking from electron micrographs based on reduced representation templates
Paper 2004Wong_ParticlePicking Model-based particle picking for cryo-electron microscopy
Paper 2004Zhu_Review Review on automatic particle picking
Paper 2007Chen_Signature Automatic particle picking program: Signature
Paper 2007Woolford_SwarmPS Automatic particle picking with several criteria, implemented in EMAN Boxer
Paper 2009Sorzano_MachineLearning Automatic particle picking based on machine learning of rotational invariants
Paper 2011Arbelaez_Comparison Evaluation of the performance of software for automated particle-boxing
Paper 2013Abrishami_MachineLearning A pattern matching approach to the automatic selection of particles from low-contrast electron micrographs
Paper 2013Hauer_2013 Automatic tilt pair detection in Random Conical Tilt
Paper 2013Hoang_ParallelGPUPicking Parallel GPU-accelerated particle picking
Paper 2013Shatsky_ParticlePicking Automated particle correspondence and accurate tilt-axis detection in tilted-image pairs
Paper 2013Vargas_ParticleQuality Automatic determination of particle quality
Paper 2014Langlois_ParticlePicking Automatic particle picking
Paper 2015Scheres_SemiAutoPicking Semi-automated selection of cryo-EM particles
Paper 2016Vilas_AutomaticTilt Automatic identification of image pairs in untilted-tilted micrograph pairs
Paper 2016Wang_DeepPicker A deep learning approach for fully automated particle picking
Paper 2017Rickgauer_Detection Picking by correlation
Paper 2017Zhu_DeepEM Deep learning approach to picking
Paper 2018Huber_Helices Automated tracing of helices
Paper 2018Heimowitz_ApplePicker Automated particle picking
Paper 2018Sanchez_DeepConsensus Deep learning consensus of multiple automatic pickers
Paper 2019Alazzawi_Clustering Use of clustering algorithms to find particles in micrographs
Paper 2019Bepler_Topaz Deep learning for particle picking
Paper 2019Carrasco_IP Use of standard image processing for particle picking
Conference 2019Li_Deep Deep learning for particle picking without box size
Paper 2019Wagner_Cryolo Deep learning for particle picking
Paper 2019Wang_Biobjective Biobjective function for robust signal detection
Paper 2019Zhang_Pixer Deep learning for particle picking
Paper 2020Sanchez_Cleaner Deep learning for removing particles from the carbon edges, aggregations, contaminations, ...
Conference 2021Li_PickerOptimizers Removal of badly picked particles with Deep Learning
Paper 2021Ohashi_GRIPS Two-pass picking with GRIPS
Paper 2022Eldar_ASOCEM Automatic segmentation of contaminations
Conference 2022Huang_DenoisingAndPicking Simultaneous denoising and picking with deep learning
Paper 2022Kreymer_MTD Expectation-Maximization approach to particle picking
Paper 2022Olek_Icebreaker Ice thickness detection and its use for particle picking
Paper 2022Zhang_EPicker Particle picking based on continual learning
Paper 2023Dhakal_CryoPPP A public database for particle picking
Paper 2023Lucas_Baited Baited reconstruction with 2D template matching
Paper 2024Anuk_Auction Particle picking using combinatorial auction
Paper 2024Cameron_REPIC Consensus 2D particle picking using graphs
Paper 2024Fang_Swin SwinCryoEM: particle picking
Paper 2024Gyawali_CryoSegNet CryoSegNet: particle picking
Paper 2024Huang_Joint Joint denoising and picking
Paper 2025Chung_CRISP Particle picking with deep learning and Conditional Random Field layers
Paper 2025Dhakal_Benchmark Benchmark of particle picking with deep learning
Paper 2025Neiterman_Frames Particle picking at the level of frames
Paper 2025Ni_GTPick GTPick: Particle picking with deep learning
Paper 2025Zamanos_CryoEMMAE Fully unsupervised particle picking using neural networks
Paper 2025Zhang_2DTMpValue p-value of the 2D template matching SNR and z-scores

2D Preprocessing

Paper 1978Carrascosa_matching Gray values matching by linear transformations
Paper 2003Rosenthal_DPR Contrast enhancement through DPR
Paper 2004Sorzano_Normalization Normalization procedures and their statistical properties.
Paper 2006Sorzano_Denoising Strong denoising in wavelet space
Conference 2009Sorzano_Downsampling Differences between the different downsampling schemes
Paper 2012Brilot_Movies Alignment of beam induced motion in direct detectors
Paper 2012Campbell_Movies Alignment of beam induced motion in direct detectors
Paper 2012Zhao_Denoising Denoising using an invariant Fourier-Bessel eigenspace
Paper 2013Norousi_Screening Screening particles to identify outliers
Paper 2013Bai_ElectronCounting Electron counting and beam induced motion correction
Paper 2013Li_ElectronCounting Electron counting and beam induced motion correction
Paper 2013Shigematsu_Movies Drift correction for movies considering dark field
Paper 2013Vargas_ParticleQuality Automatic determination of particle quality
Paper 2014Scheres_Movies Beam induced motion correction
Paper 2015Abrishami_Movies Alignment of direct detection device micrographs
Paper 2015Grant_Anisotropic Automatic estimation and correction of anisotropic magnification
Paper 2015Grant_OptimalExposure Filter movies according to the radiation damage
Paper 2015Rubinstein_Alignment Frame alignment at the level of particle
Paper 2015Spear_DoseCompensation Effect of dose compensation on resolution
Paper 2015Zhao_AnisotropicMagnification Correction of anisotropic magnification
Conference 2016Bajic_Denoising Denoising and deconvolution of micrographs
Paper 2016Jensen_RemovalVesicles Removal of vesicles in membrane proteins
Paper 2016Bhamre_Denoising Denoising by 2D covariance estimation
Paper 2017Berndsen_EMPH Automated hole masking algorithm
Paper 2017McLeod_Zorro Movie alignment by Zorro
Paper 2017Zheng_MotionCorr2 Movie alignment by MotionCorr2
Paper 2018Ouyang_Denoising Denoising based on geodesic distance
Paper 2018Wu_ContrastEnhancement Contrast enhancement
Paper 2019Zivanov_BayesianBIM Bayesian correction of beam induced movement
Paper 2020Bepler_TopazDenoise Preprocessing of micrographs for better picking
Paper 2020Chung_2SDR PCA to denoise particles
Paper 2020Chung_Prepro Preprocessing of particles for better alignment
Conference 2020Huang_SuperResolution Deep learning superresolution combination of frames
Paper 2020Palovcak_noise2noise Noise2noise denoising of micrographs
Paper 2020Strelak_FlexAlign Continuous deformation model for aligning movie frames
Conference 2021Fan_Denoising Particle denoising using vector diffusion maps
Paper 2022Heymann_ProgressiveSSNR Progressive SSNR to assess quality and radiation damage
Paper 2022Shi_Denoising Contrast estimation and denoising in SPA
Paper 2023Huang_ZSSR Multiple image super-resolution, upsampling with deep learning
Paper 2023Marshall_PCA Fast PCA on single particle images
Paper 2023Sharon_Enhancement Signal enhancement of SPA particles
Paper 2023Strelak_MovieAlignment Comparison of movie alignment programs
Paper 2023Zhang_Denoising Single Particle denoising using Deep Convolutional autoencoder and K-means++
Paper 2024Li_Subtraction Subtraction of membrane signal in SPA

2D Alignment

Paper 1981Frank_Averaging 2D averaging and phase residual
Paper 1982Saxton_Averaging 2D averaging using correlation
Paper 1998Sigworth_ML2D Maximum likelihood alignment in 2D
Paper 2003Cong_FRM2D Fast Rotational Matching in 2D
Paper 2005Cong_FRM2D Fast Rotational Matching in 2D introduced in a 3D Alignment algorithm
Paper 2005Scheres_ML2D Multireference alignment and classification in 2D
Paper 2016Aguerrebere_Limits Fundamental limits of 2D translational alignment
Paper 2010Sorzano_CL2D Multireference alignment and classification in 2D
Conference 2017Anoshina_Correlation New correlation measure for aligning images
Paper 2019Radermacher_Correlation On the properties of cross correlation for the alignment of images
Paper 2020Lederman_representation A representation theory perspective of alignment and classification
Paper 2020Marshall_Invariants Recovery of an image from its invariants
Paper 2021Chen_Fast Fast alignment through Power Spectrum
Conference 2021Chung_CryoRALIB Image alignment acceleration
Paper 2021Heimowitz_Centering Centering noisy images
Conference 2022Bendory_Complexity Computational complexity of multireference image alignment
Paper 2024Bendory_Complexity Computational complexity of multireference image alignment
Paper 2024Bai_NUFT 2D Image classification based on the Non-uniform Fourier Transform
Paper 2025Kapnulin_Outlier 2D Outlier rejection based on radial averages
Paper 2025Tang_CryoLike CryoLike: a library for fast image comparison

2D Classification and clustering

Paper 1981VanHeel_MSA Multivariate Statistical Analysis
Paper 1984VanHeel_MSA Multivariate Statistical Analysis
Paper 2005Scheres_ML2D Multireference alignment and classification in 2D
Paper 2010Sorzano_CL2D Multireference alignment and classification in 2D
Paper 2011Singer_DiffusionMaps Classification in 2D based on graph analysis of the projections
Paper 2012Yang_ISAC Iterative Stable Alignment and clustering
Paper 2014Sorzano_Outlier Outlier detection in 2D classifications.
Paper 2014Zhao_Aspire Fast classification based on rotational invariants and vector diffusion maps
Paper 2015Huang_Robust Robust w-estimators of 2D classes
Paper 2016Kimanius_Accelerated GPU Accelerated image classification and high-resolution refinement
Paper 2016Reboul_Stochastic Stochastic Hill Climbing for calculating 2D classes
Conference 2017Bhamre_Mahalanobis 2D classification using Mahalanobis distance
Paper 2017Wu_GTM 2D classification using Generative Topographic Mapping
Conference 2018Boumal_SinglePass Single pass classification
Conference 2018Shuo_Network 2D Clustering by network metrics
Paper 2020Ma_RotationInvariant 2D heterogeneity determination by rotation invariant features
Conference 2020Miolane_VAEGAN 2D Analysis by deep learning
Conference 2021Rao_Wasserstein Wasserstein K-Means for Clustering Tomographic Projections
Paper 2022Vilela_Feret 2D heterogeneity detection through Feret signatures
Paper 2022Wang_Spectral 2D classification with spectral clustering
Paper 2022Zhang_DRVAE 2D classification with deep learning and K-means++
Paper 2023Chen_Joint 2D classification with deep learning and joint unsupervised difference learning
Conference 2023Weiss_Noise Identifying non-particles with probabilistic PCA
Paper 2024Tang_SimCryoCluster SimCryoCluster: 2D classification in SPA using a deep clustering method
Paper 2025Bai_NUDFT 2D Classification in SPA using the Non-uniform DFT

3D Alignment

Paper 1980Kam_AutoCorrelation Reconstruction without angular assignment from autocorrelation function (reference free)
Paper 1986Goncharov_CommonLines Angular assignment using common lines (reference free)
Paper 1987VanHeel_CommonLines Angular assignment using common lines (reference free)
Paper 1988Provencher_Simultaneous Simultaneaous alignment and reconstruction
Paper 1988Radermacher_RCT Random Conical Tilt and Single axis tilt
Paper 1988Vogel_Simultaneous Simultaneaous alignment and reconstruction
Paper 1990Gelfand_Moments Angular assignment using moments (reference free)
Paper 1990Goncharov_Moments Angular assignment using moments (reference free)
Paper 1990Harauz_Quaternions Use of quaternions to represent rotations
Paper 1994Penczek_Real Angular assignment using projection matching in real space
Paper 1994Radermacher_Radon Angular assignment in Radon space
Paper 1996Penczek_CommonLines Angular assignment using common lines (reference free)
Paper 2003Rosenthal_DPR Angular assignment using DPR
Paper 2004Sorzano_Wavelet Angular assignment in the wavelet space.
Paper 2005Jonic_Splines Angular assignment in Fourier space using spline interpolation.
Paper 2005Yang_Simultaneous Simultaneaous alignment and reconstruction
Paper 2006Ogura_SimulatedAnnealing Angular asignment by simulated annealing
Paper 2007Grigorieff_Continuous Continuous angular assignment in Fourier space
Paper 2010Jaitly_Bayesian Angular assignment by a Bayesian method and annealing
Paper 2010Sanz_Random Random model method
Paper 2010Singer_Voting Detecting consistent common lines by voting (reference free)
Paper 2011Singer_SDP Angular assignment by semidefinite programming and eigenvectors (reference free)
Paper 2012Giannakis_Scattering Construction of an initial volume, reference free, by graph analysis of the projections
Paper 2012Shkolnisky_Sync Angular assignment by synchronization of rotations (reference free)
Paper 2013Elmlund H_PRIME PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
Paper 2013Wang_LUD Angular assignment by least unsquared deviations (reference free)
Paper 2014Vargas_RANSAC Initial model using RANSAC (reference free)
Paper 2015Joubert_Pseudoatoms Initial model based on pseudo-atoms
Paper 2015Singer_Kam Reconstruction without angular assignment from autocorrelation function (reference free)
Paper 2015Sorzano_Significant Statistical approach to the initial volume estimation (reconstruct significant)
Paper 2016Cossio_BayesianGPU GPU implementation of the Bayesian 3D reconstruction approach
Conference 2016Michels_Heterogeneous Initial volume in the presence of heterogeneity
Paper 2016Pragier_Graph Graph partitioning approach to angular reconstitution
Paper 2017Greenberg_CommonLines Common lines for reference free ab-initio reconstruction
Paper 2018Sorzano_Highres New algorithm for 3D Reconstruction and alignment with emphasis on significance
Paper 2018Sorzano_Swarm Consensus of several initial volumes by swarm optimization
Paper 2019Zehni_Joint Continuous angular refinement and reconstruction
Paper 2019Zehni_Joint Continuous angular refinement and reconstruction
Paper 2020Sharon_NonUniformKam Reconstruction and angular distribution estimation without angular assignment (reference free)
Paper 2020Xie_Network Angular assignment considering a network of assignments
Paper 2021Jimenez_DeepAlign Angular alignment using deep learning
Paper 2021Kojima_Preferred Identification of preferred orientations
Conference 2021Nashed_CryoPoseNet CryoPoseNet: Angular alignment with deep learning
Conference 2021Zhong_CryoDRGN2 CryoDRGN2: Angular alignment with deep learning
Conference 2022Levy_CryoAI CryoAI: Angular assignment through neural network
Paper 2022Lian_Neural Angular assignment through neural network
Paper 2022Lu_SphericalEmbeddings Angular assignment through common lines and spherical embeddings
Paper 2022Wang_Thunder Angular assignment implementation in GPU
Conference 2023Cesa_Alignment 3D alignment based on deep learning and equivariant representations
Paper 2023Harpaz_Alignment Fast alignment of two maps using common lines
Paper 2023Ling_Synch Synchronization of projection directions
Paper 2023Rangan_Fast Fast angular assignment using Fourier-Bessel
Paper 2023Riahi_Transport Alignment of two 3D maps using Wasserstein's distance
Paper 2024Chung_CryoForum CryoForum: Angular assignment with uncertainty estimation using neural networks
Paper 2024Muller_Common Initial volume in the presence of heterogeneity using common lines
Paper 2024Nottelet_Feret Feret signature to detect preferred orientations and misclassified images
Paper 2024Sanchez_Cesped CESPED: A benchmark for supervised particle pose estimation
Conference 2024Shekarforoush_CryoSPIN CryoSpin: Semi-amortized image alignment using deep learning
Paper 2024Singer_Wasserstein Alignment of two 3D maps using Wasserstein's distance
Paper 2024Titarenko_optimal Optimal 3D angular sampling
Paper 2024Wang_CommonLines 3D Alignment by common lines
Paper 2024Zhang_Kam Distance between maps without aligning them

3D Reconstruction

Paper 1972Gilbert_SIRT Simultaneous Iterative Reconstruction Technique (SIRT)
Paper 1973Herman_ART Algebraic Reconstruction Technique (ART)
Paper 1980Kam_SphericalHarmonics 3D Reconstruction using spherical harmonics
Paper 1984Andersen_SART Simultaneous Algebraic Reconstruction Technique (SART)
Paper 1986Harauz_FBP Exact filters for Filtered Back Projection
Chapter 1992Radermacher_WBP Exact filters for Weighted Back Projection
Paper 1997Zhu_RecCTF 3D Reconstruction (SIRT like) and simultaneous CTF correction
Paper 1998Boisset_Uneven Artifacts in SIRT and WBP under uneven angular distributions
Paper 1998Marabini_ART Algebraic Reconstruction Technique with blobs (Xmipp)
Paper 2001Sorzano_Uneven Free parameter selection under uneven angular distributions
Paper 2005Sorzano_Parameters Free parameter selection for optimizing multiple tasks
Paper 2008Sorzano_Constraints Mass, surface, positivity and symmetry constraints for real-space algorithms
Paper 2009Bilbao_ParallelART Efficient parallelization of ART
Paper 2011Li_GradientFlow Regularized 3D Reconstruction by Gradient Flow
Paper 2011Vonesch_Wavelets Fast wavelet-based 3D reconstruction
Paper 2012Gopinath_ShapeRegularization Regularized 3D Reconstruction by Shape information
Paper 2012Kucukelbir_adaptiveBasis 3D reconstruction in an adaptive basis promoting sparsity
Paper 2012Sindelar_NoiseReduction Optimal noise reduction in 3D reconstructions
Paper 2013Elmlund H_PRIME PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
Paper 2013Lyumkis_Optimod Construction of initial volumes with Optimod
Paper 2013Wang FIRM Fast 3D reconstruction in Fourier domain
Paper 2014Kunz_SART_OS Simultaneous ART with OS
Paper 2015Abrishami_Fourier 3D Reconstruction in Fourier space
Paper 2015Dvornek_SubspaceEM Fast Maximum a posteriori
Paper 2015Moriya_Bayesian Bayesian approach to suppress limited angular artifacts
Paper 2015Xu_GeometricFlow Multi-scale geometric flow
Arxiv 2016Ye_Cohomology Cohomology properties of 3D reconstruction
Paper 2017Barnett_Marching Initial volume through frequency marching
Paper 2017Punjani_CryoSPARC CryoSPARC
Paper 2017Punjani_CryoSPARCTheory Theory related to CryoSPARC
Paper 2017Sorzano_SurveyIterative Survey of iterative reconstruction methods for EM
Paper 2018Bartesaghi_Refinement Refinement of CTF, frame weight and alignment for high resolution reconstruction
Paper 2018Hu_ParticleFilter A particle filter framework for 3D reconstruction
Conference 2018Levin_Kam Ab initio reconstruction by autocorrelation analysis
Conference 2018Michels_RBF Ab-initio reconstruction with radial basis functions
Paper 2018Reboul_Simple Ab initio reconstruction with Simple
Paper 2018Sorzano_Highres New algorithm for 3D Reconstruction and alignment with emphasis on significance
Paper 2018Sorzano_Swarm Consensus of several initial volumes by swarm optimization
Paper 2018Zhu_Ewald 3D Reconstruction with Ewald sphere correction
Paper 2019Gomez_Initial Construction of initial models
Master 2019Havelkova_Regularization Regularization methods in 3D reconstruction
Paper 2019Wilkinson_Scales Combining data acquired at different scales
Paper 2020Alazzawi_Auto Automatic full processing of micrographs to yield a 3D reconstruction
Paper 2020Pan_TV 3D Reconstruction with total variation regularization
Paper 2020Punjani_NonUniform Non-uniform refinement
Paper 2020Ramlaul_Sidesplitter Local filtering along the reconstruction iterations
Paper 2020Xie_Automatic Automatic 3D reconstruction from projections
Conference 2020Venkatakrishnan_MBIR Model based image reconstruction
Paper 2020Zhou_AutomaticSelection Automatic selection of particles for 3D reconstruction
Paper 2021Abrishami_Localized Localized reconstruction in scipion expedites the analysis of symmetry mismatches in Cryo-EM data
Paper 2021Gupta_CryoGAN 3D Reconstruction via Generative Adversarial Learning
Paper 2021Luo_Opus 3D Reconstruction with a sparse and smoothness constraint
Paper 2021Kimanius_PriorKnowledge Incorporation of prior knowledge during 3D reconstruction
Paper 2021Sorzano_Uneven Algorithmic robustness to uneven angular distributions
Paper 2022Havelkova_regularization Regularization of iterative reconstruction algorithms
Conference 2022Kimanius_Sparse Sparse Fourier backpropagation
Paper 2022Lan_RCT Random Conical Tilt without picking
Paper 2023Bendory_Autocorrelation Initial volume through autocorrelation analysis with sparsity constraints
Paper 2023Geva_AbInitio Initial volume through common lines for tetahedral and octahedral symmetry
Paper 2023Herreros_ZART Correction of continuous heterogeneity during the 3D reconstruction
Paper 2023Rangan_AbInitio Robust ab initio reconstruction
Paper 2023Zhu_CryoSieve CryoSieve: Selection of the best particles to reconstruct
Paper 2024Aiyer_Workflow Workflow for the reconstruction of tilted samples
Paper 2024Huang_CryoNefen 3D reconstruction in real space with neural networks
Paper 2024Liu_kinetic A kinetic model for the resolution of the initial model using common lines
Paper 2024Suder_Workflow Workflow for the reconstruction of subparticles in highly symmetrical objects
Paper 2024Zhu_SIRM Reconstruction strategy and weights to fight preferred orientations
Paper 2025Liu_SpIsonet Deep learning approach to fighting preferential orientations during 3D reconstruction
Paper 2025Singh_Mismatch Image processing workflow to address particles with symmetry mismatches
Paper 2025Van_Probabilistic Multireference initial volume reconstruction in SPA
Paper 2025Woollard_InstaMap InstaMap: 3D reconstruction using neural networks

3D Heterogeneity

Paper 2004White_Size Heterogeneity classification of differently sized images
Paper 2006Penczek_Bootstrap 3D heterogeneity through bootstrap
Paper 2007Leschziner_Review Review of 3D heterogeneity handling algorithms
Paper 2007Scheres_ML3D Maximum Likelihood alignment and classification in 3D
Paper 2008Herman_Graph Classification by graph partitioning
Paper 2009Spahn_Bootstrap 3D heterogeneity through bootstrap
Paper 2010Elmlund_AbInitio Solving the initial volume problem with multiple conformations
Paper 2010Shatsky_MultiVariate Multivariate Statistical Analysis
Paper 2012Scheres_Bayesian A Bayesian view on cryo-EM structure determination
Paper 2012Zheng_Covariance Estimation of the volume covariance
Paper 2013Wang_MLVariance Maximum Likelihood estimate of the map variance
Paper 2013Lyumkis D_FREALIGN Likelihood-based classification of cryo-EM images using FREALIGN.
Paper 2014Chen_Migration Particle migration analysis in 3D classification
Paper 2014Dashti_Brownian Continuous heterogeneity through Brownian trajectories
Paper 2014Schwander_manifold Continuous heterogeneity through Manifold Analysis
Paper 2014Jin_NMA HEMNMA: Continuous heterogeneity through Normal Mode Analysis
Paper 2015Anden_Covariance 3D Covariance matrix estimation for heterogeneity
Paper 2015Bai_Focused Focused classification
Paper 2015Katsevich_Covariance 3D Covariance matrix estimation for heterogeneity
Paper 2015Klaholz_MRA Multivariate Statistical Analysis of Jackknife and Bootstrapping on random subsets
Paper 2015Liao_Covariance Estimation of the 3D covariance from 2D projections
Paper 2015Tagare_Direct Direct reconstruction of PCA components
Paper 2016Gong_Mechanical Mechanical model for macromolecules
Paper 2016Rawson_Movement Movement and flexibility
Paper 2016Shan_Multibody Multibody refinement
Paper 2016Sorzano_StructMap Sorting a discrete set of conformational states
Paper 2016Sorzano_Strain Calculate local stretches, strains and rotations from two conformational states
Paper 2017Punjani_CryoSPARC CryoSPARC
Paper 2017Schillbach_Warpcraft Warpcraft: 3D Reconstruction in the presence of continuous heterogeneity
Paper 2018Anden_Covariance Structural Variability from Noisy Tomographic Projections
Paper 2018Haselbach_FreeEnergy Analysis of the free energy landscape through PCA
Paper 2018Nakane_MultiBody Structural Variability through multi-body refinement
Paper 2019Serna_Review Review of classification tools
Paper 2018Solernou_FFEA Fluctuating Finite Element Analysis, continuum approach to Molecular Dynamics
Paper 2019Sorzano_Review Review of continuous heterogeneity biophysics
Paper 2019Zhang_Local Local variability and covariance
Paper 2020Dashti_Landscape Retrieving functional pathways from single particle snapshots
Conference 2020Gupta_MultiCryoGAN Reconstruction of continuously heterogeneous structures with adversarial networks
Paper 2020Harastani_NMA HEMNMA in Scipion : Using HEMNMA for analyzing continuous heterogeneity with normal modes
Paper 2020Maji_Propagation Propagation of conformational coordinates across angular space
Paper 2020Moscovich_DiffusionMaps Heterogeneity analysis by diffusion maps and spectral volumes
Paper 2020Seitz_Polaris Analysis of energy landscapes to find minimal action paths
Conference 2020Zhong_CryoDRGN CryoDRGN to analyze the continuous heterogeneity by CryoEM
Paper 2020Verbeke_Separation Heterogeneity analysis by comparing common lines
Paper 2021Chen_GM Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability
Paper 2021Giraldo_cryoBIFE A Bayesian approach to extracting free‑energy profiles
Conference 2021Hamitouche_NMADL Continuous heterogeneity analysis through normal modes and deep learning
Paper 2021Herreros_Zernikes3D Continuous heterogeneity analysis through Zernikes 3D
Paper 2021Kazemi_Enrich ENRICH: A fast method to improve the quality of flexible macromolecular reconstructions
Paper 2021Matsumoto_DEFmap Prediction of RMSF of Molecular Dynamics from a CryoEM map using deep learning
Chapter 2021Nakasako_Landscape Estimation of free-energy landscape from images
Paper 2021Punjani_3DVA 3D Variability analysis from images
Paper 2021Sorzano_PCA PCA is limited to low-resolution
Paper 2021Zhong_CryoDRGN CryoDRGN to analyze the continuous heterogeneity by CryoEM
Paper 2022Arnold_liganded Test to see if liganded states can be detected
Paper 2022Ecoffet_MorphOT More physically plausible morphing between two states
Paper 2022Gomez_Hierarchical Hierarchical classification of particles
Paper 2022Hamitouche_DeepHEMNMA DeepHEMNMA: Continuous heterogeneity analysis through normal modes and deep learning
Conference 2022Levy_CryoFire CryoFire: heterogeneity and alignment through amortized inference
Paper 2022Rabuck_Quant Workflow for discrete heterogeneity analysis
Paper 2022Seitz_ESPER ESPER through manifold embeddings
Paper 2022Skalidis_Endogenous AI tools to recognize proteins in cellular fractions
Paper 2022Wu_Manifold Continuous heterogeneity through manifold learning
Paper 2022Zhou_Data Determination of the number of discrete 3D classes
Paper 2023Barchet_Focused Applications and strategies in focused classification and refinement
Paper 2023Afonine_Varref Phenix.varref for the analysis of the model heterogeneity
Paper 2023Chen_GMM Continuous heterogeneity analysis with GMMs and neural networks
Paper 2023Dsouza_benchmark Benchmark analysis of various continuous heterogeneity algorithms
Paper 2023Esteve_Spectral Continuous heterogeneity analysis through the spectral decomposition of the atomic structure
Paper 2023Fernandez_Subtraction Subtraction of unwanted signals to improve classification and alignment
Paper 2023Forsberg_Filter Filter to estimate the local heterogeneity
Paper 2023Herreros_Hub Flexibility hub: an integrative platform for continuous heterogeneity
Paper 2023Luo_OpusDSD OPUS DSD: a neural network approach to continuous heterogeneity
Paper 2023Kinman_Analysis Analysis of the continuous heterogeneity results of CryoDrgn
Paper 2023Matsumoto_DEFmap Quantitative analysis of the prediction of RMSF from a map using DefMap
Paper 2023Punjani_3DFlex Continuous heterogeneity through 3DFlex
Paper 2023Seitz_Geometric Geometric relationships between manifold embeddings of a continuum of 3D molecular structures and their 2D projections
Paper 2023Seitz_ESPER Continuous heterogeneity through Embedded subspace partitioning and eigenfunction realignment
Paper 2023Tang_Reweighting Ensemble reweighting using Cryo-EM particles
Paper 2023Vuillemot_MDSPACE MDSPACE: Continuous heterogeneity analysis through normal modes and MD simulation
Paper 2023Wang_Autoencoder Discrete heterogeneity based on autoencoders
Paper 2024Amisaki_Multilevel Multilevel PCA for the analysis of hierarchical continuous heterogeneity
Paper 2024Chen_Focused Focused reconstruction of heterogeneous macromolecules
Paper 2024Fan_CryoTrans CryoTrans: Trajectory generation between two states
Paper 2024Klindt_Disentanglement Disentanglement of pose and conformation in the latent space of heterogeneity analysis algorithms
Conference 2024Levy_Hydra Hydra: Continuous and discrete heterogeneity using neural fields
Paper 2024Li_CryoStar CryoStar: Continuous heterogeneity analysis with structural priors
Paper 2024Schwab_DynaMight DynaMight: Heterogeneity analysis using neural networks
Paper 2024Shi_Priors Latent space priors for continuous heterogeneity
Paper 2024Song_RMSFNet RMSFNet: prediction of Molecular Dynamics RMSF from the cryoEM map
Paper 2024Yoshidome_4D Heterogeneity analysis using molecular dynamics
Paper 2025Chen_GMM Continuous heterogeneity analysis in SPA using atomic models
Paper 2025Dingeldein Amortized template matching using simulation-based inference
Paper 2025Herreros_HetSiren Discrete and Continuous heterogeneity analysis using neural networks
Paper 2025Gilles_Covariance Continuous heterogeneity analysis using regularized covariance estimation and kernel regression
Paper 2025Kinman_SIREN Heterogeneity analysis using coocurrence analysis (SIREN)
Paper 2025Lauzirika_Distinguishable How many (distinguishable) classes can we identify in single-particle analysis?
Paper 2025Levy_CryoDRGNAI CryoDRGN-AI: Heterogeneity analysis and ab initio 3D reconstruction for SPA and STA

Validation

Paper 2008Stagg_TestBed Effect of voltage, dosis, number of particles and Euler jumps on resolution
Paper 2011Henderson Tilt Validation
Paper 2011Read Validation of PDBs
Paper 2012Henderson EM Map Validation
Paper 2013Cossio_Bayesian EM Map Validation in a probabilistic setting
Paper 2013Chen_NoiseSubstitution Noise substitution at high resolution for measuring overfitting
Paper 2013Ludtke_Validation Structural validation, example of the Calcium release channel
Paper 2013Murray_Validation Validation of a 3DEM structure through a particular example
Paper 2014Russo_StatisticalSignificance EM Map Validation through the statistical significance of the tilt-pair angular assignment
Paper 2014Stagg_Reslog EM Map Validation through the resolution evolution with the number of particles
Paper 2014Wasilewski_Tilt Web implementation of the tilt pair validation
Paper 2015Heymann_Alignability EM Map Validation through the resolution of reconstructions from particles and noise
Paper 2015Oliveira_FreqLimited Comparison of gold standard and frequency limited optimization
Paper 2015Rosenthal_Review Review of validation methods
Paper 2015Wriggers_Secondary Validation by secondary structure
Paper 2016Degiacomi_IM Comparison of Ion Mobility data and EM volumes
Paper 2016Kim_SAXS Comparison of SAXS data and EM projections
Paper 2016Rosenthal_Review Review of validation methods
Paper 2016Vargas_Alignability Validation by studying the tendency of an angular assignment to cluster in the projection space
Paper 2017Monroe_PDBRefinement Validation by comparison to a refined PDB
Paper 2018Afonine_Phenix Tools in Phenix for the validation of EM maps
Paper 2018Heymann_Bsoft Map validation using Bsoft
Paper 2018Heymann_Challenge A summary of the assessments of the 3D Map Challenge
Paper 2018Jonic_Gaussian Assessment of sets of volumes by pseudoatomic structures
Paper 2018Naydenova_AngularDistribution Evaluating the angular distribution of a 3D reconstruction
Paper 2018Pages_Symmetry Looking for a symmetry axis in a PDB
Paper 2018Pintilie_SSE Evaluating the quality of SSE and side chains
Paper 2019Herzik_Multimodel Local and global quality by multi-model fitting
Paper 2020Chen_Atomic Validation of the atomic models derived from CryoEM
Paper 2020Cossio_CrossValidation Need for cross validation
Paper 2020Ortiz_CrossValidation Cross validation for SPA
Paper 2020Sazzed_helices Validation of helix quality
Paper 2020Stojkovic_PTM Validation of post-translational modifications
Paper 2020Tiwari_PixelSize Fine determination of the pixel size
Paper 2021Mendez_Graph Identification of incorrectly oriented particles
Paper 2021Pintilie_Validation Review of map validation approaches
Paper 2021Olek_FDR Cryo-EM Map–Based Model Validation Using the False Discovery Rate Approach
Paper 2022Garcia_DeepHand Checking the correct handedness with a neural network
Paper 2022Sorzano_Bias Bias, variance, gold-standard and overfitting in SPA
Paper 2022Sorzano_Validation Validation scheme and server for SPA
Paper 2022Terashi_DAQ Validation of models fitted into CryoEM maps
Paper 2022Waarshamanage_EMDA Validation of models fitted into CryoEM maps
Paper 2024Feng_DeepQs DeepQ: Local quality of the map
Paper 2024Jeon_CryoBench Datasets for heterogeneity benchmarking
Paper 2024Lytje_SAXS Validation of CryoEM maps with SAXS curves
Paper 2024Sanchez_Anisotropy New measure of anisotropy in maps
Paper 2024Verbeke_SelfFSC Self FSC: FSC with a single map
Paper 2025Bromberg_Hand Handedness validation based on the Ewald sphere
Paper 2025Pintilie_QScore Extension of Q-Score to analyze SPA maps

Resolution

Paper 1986Harauz_FBP Fourier Shell Correlation
Paper 1987Unser_SSNR 2D Spectral Signal to Noise Ratio
Paper 2002Penczek_SSNR 3D Spectral Signal to Noise Ratio for Fourier based algorithms
Paper 2003Rosenthal_DPR Review of the FSC and establishment of a new threshold
Paper 2005Unser_SSNR 3D Spectral Signal to Noise Ratio for any kind of algorithms
Paper 2005VanHeel_FSC Establishment of a new threshold for FSC
Paper 2007Sousa_AbInitio Resolution measurement on neighbour Fourier voxels
Paper 2014Kucukelbir_Local Quantifying the local resolution of cryo-EM density maps
Paper 2016Pintilie_Probabilistic Probabilistic models and resolution
Paper 2017Sorzano_FourierProperties Statistical properties of resolution measures defined in Fourier space
Conference 2018Avramov_DeepLearning Deep learning classification of volumes into low, medium and high resolution
Paper 2018Carugo_BFactors How large can B-factors be in protein crystals
Conference 2018Kim_FourierError Comparison between a gold standard and a reconstruction
Paper 2018Rupp_Problems Problems of resolution as a proxy number for map quality
Paper 2018Vilas_MonoRes Local resolution by monogenic signals
Paper 2018Yang_Multiscale Resolution from a multiscale spectral analysis
Paper 2019Avramov_DeepLearning Deep learning classification of volumes into low, medium and high resolution
Paper 2019Heymann_Statistics SNR, FSC, and related statistics
Paper 2019Ramirez_DeepRes Resolution determination by deep learning
Paper 2020Baldwin_Lyumkis_SCF Resolution attenuation through non-uniform Fourier sampling
Paper 2020Beckers_Permutation Permutation tests for the FSC
Paper 2020Penczek_mFSC Modified FSC to avoid mask induced artifacts
Paper 2020Vilas_MonoDir Local and directional resolution
Paper 2023Dai_CryoRes Local resolution through deep learning
Paper 2023Vilas_FSO Fourier Shell Occupancy to measure anisotropy
Paper 2025Urzhumtsev_RescaleFSC Rescaling of the FSC

Sharpening of high resolution information

Paper 2003Rosenthal_DPR Contrast restoration and map sharpening
Paper 2008Fernandez_Bfactor Bfactor determination and restoration
Paper 2013Fiddy_SaxtonAlgorithm Phase retrieval or extension
Paper 2014Kishchenko_SphericalDeconvolution Spherical deconvolution
Paper 2015Spiegel_VISDEM Visualization improvement by the use of pseudoatomic profiles
Paper 2016Jonic_Pseudoatoms Approximation with pseudoatoms
Paper 2016Jonic_Denoising Denoising and high-frequency boosting by pseudoatom approximation
Paper 2017Jakobi_LocScale Sharpening based on an atomic model
Paper 2019Ramlaul_Filtering Local agreement filtering (denoising)
Conference 2020Mullick_SuperResolution Superresolution from a map
Paper 2020Ramirez_LocalDeblur Local deblur (local Wiener filter)
Paper 2020Terwilliger_density Density modification of CryoEM maps
Paper 2020Vilas_Bfactor Global B-factor correction does not represent macromolecules
Paper 2021Beckers_Interpretation Improvements from the raw reconstruction to a structure to model
Paper 2021Kaur_LocSpiral LocSpiral, LocBsharpen, LocBfactor
Paper 2021Fernandez_Adjustment Map adjustment for subtraction, consensus and sharpening
Paper 2021Sanchez_DeepEMhancer Deep learning algorithm for volume restoration
Paper 2022Gilles_Wilson A molecular prior distribution for Bayesian inference based on Wilson statistics
Paper 2022Vargas_tubular Map enhancement by multiscale tubular filter
Paper 2023He_EMReady Map enhancement with local and non-local deep learning (EMReady)
Paper 2023Maddhuri_EMGan Map enhancement with GANs (EMGan)
Paper 2024Agarwal_crefDenoiser cRefDenoiser: map denoising based on deep learning
Paper 2024Kimanius_Blush Blush: data-driven regularization
Paper 2025Selvaraj_CryoTEN CryoTEN: map enhancement using transformers

CTF estimation and restoration

Paper 1982Schiske_Correction CTF correction for tilted objects
Paper 1988Toyoshima_Model CTF estimation
Paper 1995Frank_Wiener CTF correction using Wiener filter
Paper 1996Skoglund_MaxEnt CTF correction with Maximum Entropy
Paper 1996Zhou_Model CTF model and user interface for manual fitting
Paper 1997Fernandez_AR PSD estimation using periodogram averaging and AR models
Paper 1997Penczek_Wiener CTF correction using Wiener filter
Paper 1997Stark_Deconvolution CTF correction using deconvolution
Paper 1997Zhu_RecCTF CTF correction and reconstruction
Paper 2000DeRosier_EwaldCorrection CTF correction considering the Ewald sphere
Paper 2000Jensen_TiltedCorrection CTF correction considering tilt in backprojection
Paper 2001Saad_CTFEstimate CTF estimation
Paper 2003Huang_CTFEstimate CTF estimation
Paper 2003Mindell_CTFTILT CTF estimation for tilted micrographs
Paper 2003Sander_MSA CTF estimation through MSA classification of PSDs
Paper 2003Velazquez_ARMA PSD and CTF estimation using ARMA models
Paper 2004Sorzano_IDR CTF restoration and reconstruction with Iterative Data Refinement
Conference 2004Wan_CTF Spatially variant CTF
Paper 2004Zubelli_Chahine CTF restoration and reconstruction with Chahine's multiplicative method
Conference 2005Dubowy_SpaceVariant CTF correction when this is space variant
Paper 2005Mallick_ACE CTF estimation
Paper 2006Wolf_Ewald CTF correction considering Ewald sphere
Paper 2007Jonic_EnhancedPSD PSD enhancement for better identification of Thon rings; Vitreous ice diffracts in Thon rings
Paper 2007Philippsen_Model CTF Model for tilted specimens
Paper 2007Sorzano_CTF CTF estimation using enhanced PSDs
Paper 2009Sorzano_Sensitivity Error sensitivity of the CTF models, non-uniqueness of the CTF parameters
Paper 2010Jiang2010_CTFCorrection Amplitude correction method
Paper 2010Kasantsev_CTFCorrection Mathematical foundations of Kornberg and Jensen method
Paper 2010Leong_CTFCorrection Correction for spatially variant CTF
Paper 2011Glaeser_Coma The effect of coma at high-resolution
Paper 2011Mariani_Tilted CTF simulation and correction of tilted specimens
Paper 2011Sindelar_Wiener CTF correction using a modified version of Wiener filter
Paper 2011Voortman_Tilted CTF correction for tilted specimen
Paper 2012Voortman_VaryingCTF Correcting a spatially varying CTF
Paper 2013Vargas_FastDef Fast defocus
Paper 2014Penczek_CTER Estimation of the CTF errors
Paper 2015Rohou_CTFFind4 CTF Find 4
Paper 2015Sheth_CTFquality Visualization and quality assessment of CTF
Paper 2016Zhang_GCTF gCTF
Paper 2018Su_GoCTF goCTF, CTF for tilted specimens
Paper 2020Heimowitz_Aspire CTF determination in Aspire
Paper 2020Zivanov_HighOrder Estimation of high-order aberrations
Paper 2022Pant_ExitWave Estimation of the electron exit-wave
Paper 2023Fernandez_Local Local defocus estimation
Paper 2025Elferich_CTFFind5 Quality, tilt, and thickness of TEM samples with CTFFind5

Segmentation

Paper 2006Baker_segmentation Segmentation of molecular subunits
Paper 2010Pintilie_segger Segmentation of molecular subunits
Conference 2017Nissenson_VolumeCut Segmentation of an EM volume using an atomic model
Paper 2019Beckers_FDR Segmentation of the protein using False Discovery Rate
Paper 2020Beckers_FDR Segmentation of the protein using False Discovery Rate (GUI)
Paper 2020Farkas_MemBlob Segmentation of membrane in membrane embedded proteins
Paper 2020Terashi_MainMastSeg Segmentation of proteins into domains
Paper 2022Ranno_Neural Neural representation of a map
Paper 2021He_EMNUSS EMNUSS: Identification of secondary structure in CryoEM maps with deep learning
Paper 2024Sazzed_CryoSSESeg CryoSSESeg: Identification of secondary structure in CryoEM maps with deep learning
Paper 2025Cao_EMInfo EMInfo: Segmentation of secondary structure and nucleic acids in CryoEM maps

Fitting and docking

Paper 1999Volkmann_Fitting Fitting in real space
Paper 2001Baker_Review Review of protein structure prediction
Paper 2001Jones_Review Review of protein structure prediction
Paper 2003Kovacs_FRM3D Fast Rotational Alignment of two EM maps
Paper 2004Tama_NMA1 Flexible fitting with Normal Modes (I)
Paper 2004Tama_NMA2 Flexible fitting with Normal Modes (II)
Paper 2005Velazquez_Superfamilies Recognition of the superfamily folding in medium-high resolution volumes
Paper 2007DeVries_Haddock Docking with Haddock 2.0
Paper 2007Kleywegt_QualityControl Quality control and validation of fitting
Paper 2008Orzechowski_Flexible Flexible fitting with biased molecular dynamics
Paper 2008Rusu_Interpolation Biomolecular pleiomorphism probed by spatial interpolation of coarse models
Paper 2012Biswas_Secondary Secondary structure determination in EM volumes
Paper 2012Velazquez_Constraints Multicomponent fitting by using constraints from other information sources
Paper 2013Chapman MS_Atomicmodeling Atomic modeling of cryo-electron microscopy reconstructions--joint refinement of model and imaging parameters
Paper 2013Esquivel_Modelling Review on modelling (secondary structure, fitting, ...)
Paper 2013Lopez_Imodfit Fitting based on vibrational analysis
Paper 2013Nogales_3DEMLoupe Normal Mode Analysis of reconstructed volumes
Paper 2014AlNasr_Secondary Identification of secondary structure elements in EM volumes
Paper 2014Politis_MassSpect Integration of mass spectroscopy information
Paper 2014Rey_MassSpect Integration of mass spectroscopy information
Paper 2014Villa_Review Review of atomic fitting into EM volumes
Paper 2015Barad_EMRinger Validation of hybrid models
Paper 2015Bettadapura_PF2Fit Fast rigid fitting of PDBs into EM maps
Paper 2015Carrillo_CapsidMaps Analysis of virus capsids using Google Maps
Paper 2015Hanson_Continuum Modelling assemblies with continuum mechanics
Paper 2015Lopez_Review Review of structural modelling from EM data
Paper 2015Schroeder_Hybrid Review on model building
Paper 2015Tamo_Dynamics Dynamics in integrative modeling
Paper 2015Sorzano_AtomsToVoxels Accurate conversion of an atomic model into a voxel density volume
Paper 2016Joseph_Evolution Evolutionary constraints for the fitting of atomic models into density maps
Paper 2016Joseph_Refinement Refinement of atomic models in high-resolution EM reconstructions using Flex-EM
Paper 2016Murshudov_Refinement Refinement of atomic models in high-resolution EM reconstructions
Paper 2016Segura_3Diana Validation of hybrid models
Paper 2016Singharoy_MDFF Construction of hybrid models driven by EM density and molecular dynamics
Paper 2016Wang_Rosetta Construction of hybrid models driven by EM density using Rosetta
Paper 2017Chen_CoarseGraining Coarse graining of EM volumes
Paper 2017Joseph_Metrics Metrics analysis for the comparison of structures
Paper 2017Hryc_WeightedAtoms Construction of hybrid models by locally weighting the different atoms
Paper 2017Matsumoto_Distribution Estimating the distribution of conformations of atomic models
Paper 2017Michel_ContactPrediction Structure prediction by contact prediction
Paper 2017Miyashita_EnsembleFitting Ensemble fitting using Molecular Dynamics
Paper 2017Turk_ModelBuilding Tutorial on model building and protein visualization
Paper 2017Wang_PartialCharges Appearance of partial charges in EM maps
Paper 2017Wlodawer Comparison of X-ray and EM high resolution structures
Paper 2018Cassidy_review Review of methods for hybrid modeling
Paper 2018Chen_SudeChains A comparison of side chains between X-ray and EM maps
Paper 2018Kawabata_Pseudoatoms Modelling the EM map with Gaussian pseudoatoms
Paper 2018Kovacs_Medium Modelling of medium resolution EM maps
Paper 2018Neumann_validation Validation of fitting, resolution assessment and quality of fit
Paper 2018Terwilliger_map_to_model Phenix map_to_model, automatic modelling of EM volumes
Paper 2018Wang_MD Constructing atomic models using molecular dynamics
Paper 2018Xia_MVPENM Multiscale Normal Mode Analysis
Paper 2018Yu_Atomic Constructing atomic models using existing tools
Paper 2019Bonomi_Multiscale Bayesian multi-scale modelling
Paper 2019Kidmose_Namdinator Namdinator: Flexible fitting with NAMD
Paper 2019Kim_CryoFit CryoFit: flexible fitting in Phoenix
Paper 2019Klaholz_Review Review of Phenix tools to modelling
Paper 2019Subramaniya_DeepSSE Secondary structure prediction from maps using deep learning
Paper 2019Zhang_CoarseGrained Coarse-graining of EM maps
Paper 2020Costa_MDeNM Flexible fitting with molecular dynamics and normal modes
Paper 2020Cragnolini_Tempy2 TEMpy2 library for density-fitting and validation
Paper 2020Dodd_ModelBuilding Model building possibilities, with special emphasis on flexible fitting
Paper 2020Ho_CryoID Identification of proteins in structural proteomics from cryoEM volumes
Paper 2020Hoh_Buccaneer Structure modelling with Buccaneer
Paper 2020Joseph_comparison Comparison of map and model, or two maps
Paper 2020Kim_Review Review of the options for atomic modelling
Paper 2020Leelananda_Constraints NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD structure refinement
Paper 2020Liebschner_Ceres CERES: Web server of refined atomic maps of CryoEM deposited maps by Phenix
Paper 2020Oroguchi Assessment of Force Field Accuracy Using Cryogenic Electron Microscopy Data
Paper 2020Vant_Flexible Flexible fitting with molecular dynamics and neural network potentials
Paper 2021Behkamal_Secondary Secondary structure from medium resolution maps
Paper 2021Chojnowski_quality Quality of models automatically fitted with ARP/wARP
Paper 2021Han_Vesper VESPER: global and local cryo-EM map alignment using local density vectors
Paper 2021Lawson_Challenge Validation recommendations based on outcomes of the 2019 EMDataResource challenge
Paper 2021Mori_Flexible Efficient Flexible Fitting Refinement with Automatic Error Fixing
Paper 2021Pfab_DeepTracer DeepTracer for fast de novo cryo-EM protein structure modeling
Paper 2021Saltzberg_IMP Using the Integrative Modeling Platform to model a cryoEM map
Paper 2021Terwilliger_CryoID Identification of sequence in a CryoEM map from a set of candidates
Paper 2021Titarenko_LocalCorr Performance improvement of local correlation for docking
Conference 2021Vuillemot_NMA Flexible fitting using a combined Bayesian and Normal Mode approach with Hamiltonian Monte Carlo sampling
Paper 2022Antanasijevic_ab Sequence determination of antibodies bound to a map
Paper 2022Behkamal_LPTD LPTD: Topology determination of CryoEM maps
Paper 2022Bouvier_coevolution Atomic modelling exploiting residue coevolution
Paper 2022Chojnowski_findMySeq Identify sequence in CryoEM map using Deep Learning
Paper 2022Hryc_Pathwalking Atomic modelling with Pathwalking
Paper 2022He_EMBuild Atomic modelling for complexes with EMbuild
Paper 2022Krieger_Prody2 Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0
Paper 2022Neijenhuis_Haddock Protein-protein interface refinement in complex maps with Haddock2.4
Paper 2022Terwilliger_AlphaFold Iterative modelling with AlphaFold and experimental maps
Paper 2022Urzhumtsev_Direct Calculation of the EM map from an atomic model
Paper 2022Urzhumtsev_XrayEM Effect of the local resolution on the atomic modeling
Paper 2022Vuillemot_NMMD NMMD: Flexible fitting with simultaneous Normal Mode and Molecular Dynamics displacements
Paper 2022Zhang_CRITASSER Atomic models of assemble protein structures with deep learning
Paper 2023Blau_FittingML Maximum-likelihood fitting of atomic models in EM maps
Paper 2023Chang_CryoFold Flexible fitting into cryo-EM maps with CryoFold (a MELD plugin)
Paper 2023Dai_CryoFEM CryoFEM: Deep learning+AlphaFold 2 for the interpretation of maps
Paper 2023Millan_LL Likelihood-based docking of models into cryo-EM maps
Paper 2023Park_CSA Atomic model fitting using conformational space annealing
Paper 2023Read_LL Likelihood-based signal and noise analysis for docking of models into cryo-EM maps
Paper 2023Reggiano_MEDIC Evaluation of atomic models using MEDIC
Paper 2023Richardson_Overfitting Evaluation of overfitting errors in model building
Paper 2023Sweeney_ChemEM ChemEM: Flexible Docking of Small Molecules in Cryo-EM Structures
Paper 2023Terashi_DAQrefine Atomic model refinement using AlphaFold2 and DAQ
Paper 2023Terashi_DeepMainMast DeepMainMast: de novo modelling of CryoEM maps
Paper 2023Terwilliger_AlphaFold Comparison of AlphaFold predictions with experimental maps and models
Paper 2023Wang_CryoREAD CryoREAD: de novo modelling of nucleic acids
Paper 2024Beton_Ensemble Ensemble fitting
Paper 2024Chen_EModelX Atomic modelling de novo from cryoEM maps
Paper 2024Dahmani_MDFF Accelerated MDFF flexible fitting
Paper 2024Giri_CryoStruct CryoStruct: de novo modeling of cryoEM maps
Paper 2024Gucwa_CMM CheckMyMetal: Metal analysis in CryoEM maps
Paper 2024Jamali_Modelangelo ModelAngelo: Automated model building of cryoEM maps
Paper 2024He_SHOT Accurate global and local 3D alignment of cryo-EM density maps using local spatial structural features
Paper 2024Hoff_EMMIVox EMMIVox: Model fitting using ensembles and molecular dynamics
Paper 2024Li_EMRNA EMRNA: de novo modeling of RNA structures
Paper 2024Li_EM2NA EM2NA: Detection and de novo modelling of nucleic acids in cryoEM maps
Paper 2024Read_Interactive Interactive local docking
Paper 2024Wang_DiffModeller CryoEM map modelling integrating AlphaFold2 and diffusion networks
Paper 2024Wankowicz_qFit Multiconformer modeling of cryoEM maps
Paper 2024Wlodarski_cryoEnsemble CryoEnsemble: cryoEM map interpretation with molecular dynamics simulated ensembles
Paper 2025Carr_Map2Seq Map-to-sequence workflow
Paper 2025Chen_CryoEvoBuilding CryoEvoBuilding: Model building for intermediate resolution maps using evolutionary information
Paper 2025Chen_GMMs Model building in heterogeneous maps
Paper 2025Haloi_Ligand Ligand detection in CryoEM maps using structure prediction and flexible fitting
Paper 2025Karolczak_Ligand Ligand detection in CryoEM maps using deep learning
Paper 2025Li_EMProt EMProt: atomic modelling of cryoEM maps using deep learning
Paper 2025Luo_DiffFit DiffFit: Flexible fitting of map and atomic model
Paper 2025Mallet_crAI crAI: detection of antibodies in cryoEM maps
Paper 2025Matsuoka_ForceConstant Empirical determination of the force constant for flexible fitting
Paper 2025Muenks_EmeraldID Emerald ID: Identification of small ligands in cryoEM maps
Paper 2025Riahi_EMPOT EMPOT: aligning partially overlapping maps using Unbalanced Gromov-Wasserstein Divergence
Paper 2025Shub_Mic Mic: a deep learning algorithm to assign ions and waters in SPA maps
Paper 2025Su_CryoAtom CryoAtom: Model building using deep learning
Paper 2025Wang_E3CryoFold E3CryoFold: model building in cryoEM maps
Paper 2025Zhang_Emol Emol: modeling protein-nucleic acid complex structures from cryo-EM maps
Paper 2025Zhang_Benchmark Benchmarking multiple algorithms to compute an atomic model from a cryoEM map
Paper 2025Zheng_Disorder Exploration of disordered regions in CryoEM maps
Paper 2026Mulvaney_CASP16 Relationship between local resolution, RMSF, pLDDT and SMOC in CASP16 CryoEM maps

Books and reviews

Book 1980Herman_Tomography General book on tomography
Book 1988Kak_Tomography General book on tomography
Paper 2000Tao_Review Review of single particles
Paper 2000VanHeel_Review Review of single particles
Paper 2002Frank_Review Review of single particles
Paper 2002Schmid_Review Review of single particles
Paper 2004Henderson_Review Review of electron microscopy
Paper 2004Subramaniam_Review Review of single particles
Paper 2005Steven_Review Review of electron microscopy
Paper 2006Fernandez_Review Review of electron microscopy
Book 2006Frank_book Book covering all aspects of electron microscopy of single particles
Paper 2006Sorzano_Review Review of optimization problems in electron microscopy
Paper 2007Leschziner_Review Review of 3D heterogeneity handling algorithms
Paper 2007Sorzano_Review Review of the image processing steps
Paper 2008Fanelli_ImageFormation Review on the image formation model from the electron waves and open inverse-problems in Electron Tomography
Paper 2008Fernandez_HPCReview High performance computing in electron cryomicroscopy
Paper 2008Jonic_Review Comparison between electron tomography and single particles
Paper 2008Mueller_Review Review of Electron microscopy
Paper 2008Taylor_Review Review of Electron microscopy
Paper 2010DeRosier_Review Personal account of how 3DEM developed in the early days
Chapter 2012Sorzano_Review Review of single particle analysis using Xmipp
Chapter 2012Devaux_Protocol Protocols for performing single particle analysis
Paper 2014Bai_Review Recent advances in cryo-EM
Paper 2015Carazo_Review Review of the reconstruction process
Paper 2015Cheng_Review A primer to Single Particle Cryo-EM
Paper 2015Cheng_Reviewb Single Particle Cryo-EM at crystallographic resolution
Paper 2015Elmlund_Review Recent advances in cryo-EM
Paper 2015Henderson_Review Recent advances in cryo-EM
Paper 2015Nogales_Review Recent advances in cryo-EM
Paper 2015Schroeder_Review Review of advances in the electron microscope
Paper 2015VanDenBedem_Integrative Review of integrative structural biology
Paper 2015Wu_Review Review of advances in cryo-EM
Paper 2016Carroni_CryoEM Review of advances in Cryo-EM
Paper 2016Egelman_CryoEM Review of advances in Cryo-EM
Paper 2016Eisenstein_CryoEM News feature on the Method of the Year
Paper 2016FernandezLeiro_Review Review of EM
Paper 2016Glaeser_HowGood How good can cryo-EM become?
Paper 2016Jonic_PseudoAtoms Review of the applications of the use of pseudoatoms in EM
Chapter 2016Mio_Review Overview of the process to obtain EM reconstructions
Paper 2016Jonic_Review A review of computational ways to handle heterogeneity
Paper 2016Nogales_Review Review of advances in cryo-EM
Paper 2016Subramaniam_Review Why cryo-EM is now suitable for crystallographic journals
Paper 2016Vinothkumar_Review Historical review and current limitations
Report 2017Brezinski_Nobel Scientific background on the Nobel Prize in Chemistry 2017
Paper 2017Cheng_review Why CryoEM became so hot
Paper 2017Danev_Review Review of the use of phase plates in EM
Paper 2017Elmlund_Review Review of the main current difficulties of EM
Paper 2017Frank_Review Historical review of EM
Paper 2017Frank_TimeResolved Review of time-resolved of EM
Paper 2017Jonic_Review Review of computational methods to analyze conformational variability
Paper 2017Merino_DrugEM Applications of EM for drug design
Paper 2017Rawson_Limitations Limitations of EM for drug design
Paper 2017Sorzano_FourierProperties Review of statistical properties of resolution measures defined in Fourier space
Paper 2017Sorzano_SurveyIterative Survey of iterative reconstruction methods for EM
Paper 2018Bruggeman_Crowdsourcing Exploring crowdsourcing for EM image processing
Paper 2018Cheng_Review Review of EM and future ahead
Paper 2018Cossio_ML Review of Maximum Likelihood methods
Paper 2018Grimes_Crystallography Review of X-ray crystallography and its relationship to EM
Paper 2018Murata_Review Review of EM for structure dynamics
Paper 2018Quentin_Biomedical Review of EM as a tool for biomedical research
Paper 2018Scapin_DrugDiscovery Review of EM as a tool for drug discovery
Paper 2018Vilas_ImageProcessing Review of the recent developments in image processing for single particle analysis
Paper 2018vonLoeffelholz_VPP Comparison of Volta Phase Plate reconstructions close to focus and with defocus
Paper 2018Eisenstein_DrugDesigners Drug designers embrace cryo-EM
Paper 2019Benjin_Review Review of SPA
Paper 2019Danev_Review Review of future directions
Paper 2019Lyumkis_Review Challenges and reviews
Paper 2019Sorzano_Review Review of continuous heterogeneity biophysics
Paper 2019Urzhumtseva_Review Review of rotation conventions
Paper 2020Abriata_Review Considerations of structure prediction and CryoEM
Paper 2020Akbar_Review Review of membrane protein reconstructions
Paper 2020Bendory_Review Review of image processing problems
Paper 2020Dubach_Review Review of resolution in X-ray crystallography and CryoEM
TechReport 2020Lai_Statistics Review of statistical properties of image alignment
Paper 2020Hu_Quaternions Review of the use of quaternions to describe rotations
Paper 2020McCafferty_Review Review of SPA and Mass Spectroscopy
Paper 2020Seffernick_Hybrid Review of hybrid (computational and experimental) methods to get protein structure
Paper 2020Nakane_Atomic Single-particle cryo-EM at atomic resolution
Paper 2020Singer_Sigworth_Review Review of single particle analysis
Paper 2020Vilas_Review Review of local resolution
Paper 2020Wigge_Review Review of drug discovery with CryoEM
Paper 2020Wu_Review Review of current limitations, with special emphasis on protein size
Paper 2021Bai_Review Review of breakthroughs leading to atomic resolution
Paper 2021DImprima_Review Review of sample preparation for single particle analysis
Paper 2021Lander_Review Review of focused analysis in SPA
Paper 2021Raimondi_Review General review of SPA
Paper 2022Beton_Fitting Review of fitting in SPA
Paper 2022Burley_PDB Review of cryoEM derived structures at PDB
Paper 2022Caldraft_Tilt Review of applications of tilt pairs in SPA
Paper 2022Donnat_GAN Review of Generative modelling with neural networks
Paper 2022Guaita_Review Recent advances and current trends in cryo-electron microscopy
Paper 2022Jones_Comment Comment on the impact of AlphaFold and next challenges ahead
Paper 2022Namba_Review Review of the current state of SPA
Paper 2022Ourmazd_Comment Comment on the impact of AlphaFold and next challenges ahead
Paper 2022Palmer_Local Review of local methods in CryoEM
Paper 2022Sorzano_1000 CryoEM is the field of 1000+ methods
Paper 2022Subramaniam_Comment Comment on the impact of AlphaFold and next challenges ahead
Paper 2022Treder_DL Review of Deep Learning applications in CryoEM
Paper 2022Vant_MD Review of Molecular Dynamics analysis of CryoEM maps
Paper 2023Amann_TimeResolved Review of time-resolved cryoEM
Paper 2023Bai_Challenges Challenges and opportunities in structure determination
Paper 2023Beton_Fitting Review of fitting tools in cryoEM
Paper 2023DiIorio_AbInitio Review of ab initio reconstruction algorithms based on deep learning
Paper 2023Liu_AWI Review of the Air-Water Interface
Paper 2023Lucas_Structureome Review of the localization of proteins and complexes in their cellular context
Paper 2023Miyashita_MD Review of the use of molecular dynamics in atomic modelling
Paper 2023Si_DeNovo Review of the de-novo atomic modelling
Paper 2023Tang_Conformational Review of conformational heterogeneity and probability distributions
Paper 2023Toader_Heterogeneity Review of continuous heterogeneity
Paper 2024Bock_MD Review of the joint use of Molecular Dynamics and CryoEM
Paper 2024Bowlby_Flexible Review of continuous flexibility
Paper 2024Cheng_Automated Review of automated acquisition
Paper 2024Kimanius_Heterogeneity Review of heterogeneity analysis
Paper 2024Lander_Validation Review of SPA validation
Paper 2024Riggi_Animation Review of 3D animation as a tool for integrative modeling
Paper 2025Farheen_Modeling Review of structure modeling
Paper 2025Kim_Review Review of SPA and protein-protein or protein-ligand docking
Paper 2025Leone_Review Review of the integration of Molecular Dynamics with experimental techniques
Paper 2025Patwardhan_Extending Perspective on technological developments leading to a wider application of cryoEM
Paper 2025Wan_CryoETStandards Perspective on the need for CryoET standards
Paper 2025Zhu_Quality Review of AI-based quality assessment of SPA maps

Software

Paper 1996Frank_Spider Spider
Paper 1996VanHeel_Imagic Imagic
Paper 1999Lutdke_Eman Eman
Paper 2004Sorzano_Xmipp Xmipp
Paper 2007Baldwin_AngularTransformations The Transform Class in SPARX and EMAN2
Paper 2007Heymann_Bsoft Bsoft
Paper 2007Grigorieff_Frealign Frealign
Paper 2008Scheres_XmippProtocols Xmipp Protocols
Paper 2008Shaikh_SpiderProtocols Spider Protocols
Paper 2012Wriggers_SitusConventions Conventions and workflows in Situs
Paper 2013DeLaRosa_Xmipp30 Xmipp 3.0
Paper 2015Cianfrocco_Cloud Software execution in the cloud
Paper 2015Cheng_MRC2014 Extensions to MRC file format
Paper 2013DeLaRosa_Scipion Scipion
Paper 2016Scheres_Relion Tutorial on the use of Relion
Paper 2016Grigorieff_Frealign Tutorial on the use of Frealign
Paper 2017Moriya_Sphire Tutorial on the use of Sphire
Paper 2018Bell_EMAN2 New tools in EMAN2
Paper 2018Cianfrocco_cloud CryoEM Cloud Tools
Paper 2018Grant_cisTEM cisTEM
Paper 2018McLeod_MRCZ MRC Compression format
Paper 2018Zivanov_Relion3 Relion 3
Paper 2020Caesar_Simple3 Simple 3
Paper 2021Baldwin_SCF Visualizer of the Sampling Compensation Factor
Paper 2021Jimenez_Scipion Scipion workflow example for image processing
Paper 2021Kimanius_Relion4 Changes in Relion 4.0
Paper 2021Maji_BlackBox Exploration of image processing concepts
Paper 2021Sharov_Relion Use of Relion within Scipion
Paper 2021Sorzano_Scipion Use of Scipion as a way to compare the results of multiple methods
Paper 2021Strelak_Xmipp Advances in Xmipp
Paper 2022DiIorio_Multiple A Robust Single-Particle Cryo-Electron Microscopy (cryo-EM) Processing Workflow with cryoSPARC, RELION, and Scipion.
Paper 2022Fluty_Precision Precision requirements and data compression
Paper 2022Harastani_ContinuousFlex ContinuousFlex: Software for continuous heterogeneity analysis in cryo-EM and cryo-ET
Paper 2022Warshamanage_EMDA A Python library for low-level computations such as local correlation
Paper 2023Cheng_AutoEMage AutoEMage: a system for processing in streaming (SPA)
Paper 2023Conesa_Scipion3 Scipion3: A workflow engine for cryoEM
Paper 2023Krieger_ScipionPrody Scipion-EM-Prody: Interface between Scipion and Prody (Structural Analysis)
Paper 2023Matinyan_TRPX TRPX compression format
Paper 2023Short_MRC2020 MRC2020: improvements to Ximdisp and the MRC image-processing programs
Paper 2024deLaRosa_EMHub A web-based Laboratory Information Management System for cryoEM facility
Paper 2024Gonzalez_Dashboard A web-based dashboard for Relion
Paper 2024Herre_Capsules SBGrid Capsules to execute programs in controlled environments
Paper 2024Moriya_GoToCloud GoToCloud: SPA processing in the cloud
Paper 2024Urzhumtseva_VUE VUE: Visualization of angular distributions
Paper 2024Vuillemot_MDSPACE MDSpace and MDTomo to analyze continuous heterogeneity
Paper 2025Chen_CryoCRAB CryoCRAB: a large database of curated micrographs
Conference 2025Fu_T2Relion T2-Relion: Task-parallelism, Tensor-core acceleration of Relion
Paper 2025Khoshbin_Magellon Magellon: a software platform for CryoEM image processing
Paper 2025Matinyan_TRPX TRPX v2: fast compression of raw files

Electron tomography

Data Collection

Paper 2025Sharma_DataCollection Automation for cryo-electron tomography data collection

Image preprocessing

Paper 2015Yan_thickness Determination of thickness, tilt and electron mean free path
Paper 2018Wu_contrast Contrast enhancement to improve alignability

Image alignment

Paper 1982Guckenberger_commonOrigin Determination of a common origin in the micrographs of titl series in three-dimensional electron microscopy
Paper 1992Lawrence_leastSquares Least squares solution of the alignment problem
Paper 1995Penczek_dual Dual tilt alignment
Paper 1996Owen_alignmentQuality Automatic alignment without fiducial markers and evaluation of alignment quality
Paper 1998Grimm_normalization Discussion of several gray level normalization methods for electron tomography
Paper 2001Brandt_Automatic1 Automatic alignment without fiducial markers
Paper 2001Brandt_Automatic2 Automatic alignment with fiducial markers
Paper 2006Winkler_alignment Marker-free alignment and refinement
Paper 2006Castano_alignment Alignment with non-perpendicularity
Paper 2007Castano_alignment Fiducial-less alignment of cryo-sections
Paper 2009Sorzano_alignment Marker-free alignment and refinement
Paper 2010Cantele_dualAlignment Alignment of dual series
Paper 2014Tomonaga_Automatic Automatic alignment of tilt series using the projection themselves
Paper 2014Han_Automatic Automatic alignment of tilt series using SIFT features
Paper 2015Han_Automatic Automatic alignment of tilt series using fiducials
Paper 2017Mastronarde_Automatic Automatic alignment and reconstruction of tilt series in IMOD
Paper 2018Fernadez_Beam Image alignment considering beam induced motion
Paper 2018Han_Fast Automatic alignment using fiducial markers
Paper 2019Fernandez_residual Alignment of tilt series using residual interpolation
Paper 2019Han_Dual Automatic alignment using fiducial markers in dual tilt series
Paper 2020Sorzano_automatic Automatic alignment considering several geometrical distortions
Paper 2021Han_LocalConstraints Automatic alignment considering local constraints
Paper 2022Ganguly_SparseAlign Sparse Align: Automatic detection of markers and deformation estimation
Paper 2022Zheng_Aretomo Automatic alignment based on projection matching
Paper 2024Coray_Automated Automated fiducial-based tilt series alignment in Dynamo
Paper 2024deIsidro_deep Detection of tilt series misalignment in the reconstructed tomogram using a neural network
Paper 2024Hou_Marker Marker detection using wavelets
Paper 2024Xu_MarkerAuto2 MarkerAuto2: Tilt series alignment using fiducials
Paper 2025deIsidro_Misalignment Tilt series misalignment detection
Paper 2025Guo_Alignment Tilt series alignment with L1-norm optimization

CTF estimation and restoration

Paper 2003Winkler_CTF Focus gradient correction in electron tomography
Paper 2006Fernandez_CTF CTF determination and correction in electron tomography
Paper 2009Zanetti_CTF CTF determination and correction in electron tomography
Paper 2009Xiong_CTF CTF determination and correction for low dose tomographic tilt series
Paper 2012Eibauer_CTF CTF determination and correction
Paper 2015Bharat_CTFCorrectedSubtomogramAveraging Subtomogram averaging with CTF correction using a Bayesian prior
Paper 2017Turonova_3DCTF 3D CTF Correction
Paper 2017Kunz_3DCTF 3D CTF Correction
Paper 2024Mastronarded_CTFPlotter CTF estimation with CTFPlotter
Paper 2024Zhang_CTFMeasure Simultaneous CTF estimation for a whole tilt series
Paper 2025Khavnekar_PSD Accurate PSD determination in tilt series

3D reconstruction

Paper 1972Gilbert_SIRT Simultaneous Iterative Reconstruction Technique (SIRT)
Paper 1973Herman_ART Algebraic Reconstruction Technique (ART)
Paper 1984Andersen_SART Simultaneous Algebraic Reconstruction Technique (SART)
Paper 1992Radermacher_WBP Weighted Backprojection in electron tomography
Paper 1997Marabini_reconstruction Iterative reconstruction in electron tomography
Paper 2002Fernandez_reconstruction Iterative reconstruction in electron tomography
Paper 2007Radermacher_WBP Weighted Backprojection in electron tomography
Paper 2008Fernandez_CARP Component Averaged Row Projections (CARP)
Paper 2010Xu_Long Iterative reconstructions with long object correction and GPU implementation
Paper 2012Herman General Superiorization Superiorization: an optimization heuristic for medical physics
Paper 2012Zhang_IPET_FETR IPET and FETR, a reconstruction algorithm for a single particle structure determination without any averaging
Paper 2013Goris_SIRT_TV_DART Combination of SIRT, Total Variation and Discrete ART to reconstruct and segment at the same time
Paper 2013Briegel A_Challenge The challenge of determining handedness in electron tomography and the use of DNA origami gold nanoparticle helices as molecular standards
Paper 2013Messaoudi_EnergyFiltered 3D Reconstruction of Energy-Filtered TEM
Paper 2014Paavolainen_Missing Compensation of the missing wedge
Paper 2015Venkatakrishnan_MBIR 3D Reconstruction with priors
Paper 2016Deng_ICON 3D Reconstruction with missing information restoration
Paper 2016Guay_Compressed 3D Reconstruction using compressed sensing
Paper 2016Turonova_Artifacts Artifacts observed during 3D reconstruction
Paper 2019Yan_MBIR 3D Reconstruction with priors and demonstration of its use in biological samples
Paper 2020Sanchez_Hybrid 3D reconstruction with a special acquisition and alignment scheme
Paper 2020Song_Tygress 3D reconstruction with a special acquisition and alignment scheme
Paper 2021Fernandez_TomoAlign 3D reconstruction with sample motion and CTF correction
Paper 2021Geng_Nudim Non-uniform FFT reconstruction and total variation to fill the missing wedge
Paper 2024vanVeen_Missing Missing wedge filling in cryoET
Paper 2025Debarnot_IceTide 3D Reconstruction in CryoET with local deformation corrections and neural networks

Noise reduction

Paper 2001Frangakis_NAD Noise reduction with Nonlinear Anisotropic Diffusion
Paper 2003Fernandez_AND Anisotropic nonlinear diffusion for electron tomography
Paper 2003Jiang_Bilateral Bilateral denoising filter in electron microscopy
Paper 2005Fernandez_AND Anisotropic nonlinear denoising in electron tomography
Paper 2007Heide_median Iterative median filtering in electron tomography
Paper 2007Fernandez_autAND Anisotropic nonlinear diffusion with automated parameter tuning
Paper 2009Fernandez_Beltrami Nonlinear filtering based on Beltrami flow
Paper 2010Bilbao_MeanShift Mean Shift Filtering
Paper 2014Kovacik_wedgeArtefacts Removal of wedge artefacts
Paper 2014Maiorca_beadArtefacts Removal of gold bead artefacts
Paper 2018Trampert_Inpainting Removal of the missing wedge by inpainting
Paper 2018Moreno_TomoEED Fast Anisotropic Diffusion
Paper 2018Wu_Enhancement Enhancing the image contrast of electron tomography
Paper 2022Liu_Isonet Isotropic reconstructions using deep learning
Paper 2024vanBlerkom_GoldX GoldX: Gold bead removal
Paper 2025Costa_CryoSamba CryoSamba: tomogram denoising

Segmentation

Paper 2002Frangakis_Eigenanalysis Segmentation using eigenvector analysis.
Paper 2002Volkmann_Watershed Segmentation using watershed transform.
Paper 2003Bajaj_BoundarySegmentation Segmentation based on fast marching.
Paper 2005Cyrklaff_Thresholding Segmentation using optimal thresholding.
Paper 2007Lebbink_TemplateMatching Segmentation using template matching.
Paper 2007Sandberg_OrientationFields Segmentation using orientation fields.
Paper 2007Sandberg_SegmentationReview Review on segmentation in electron tomography.
Paper 2008Garduno_FuzzySegmentation Segmentation using fuzzy set theory principles.
Paper 2009Lebbink_TemplateMatching2 Segmentation using template matching.
Paper 2012RubbiyaAli_EdgeDetection Parameter-Free Segmentation of Macromolecular Structures.
Paper 2014Martinez-Sanchez_TomoSegMemTV Membrane segmentation.
Conference 2015Xu_TemplateMatching Detection of macromolecular complexes with a reduced representation of the templates.
Paper 2017Ali_RAZA Automated segmentation of tomograms
Paper 2017Chen_Annotation Automated annotation of tomograms
Paper 2017Tasel_ActiveContours Segmentation with active contours
Paper 2017Xu_DeepLearning Finding proteins in tomograms using deep learning
Paper 2018Zeng_DeepLearning Mining features in Electron Tomography by deep learning
Paper 2020Salfer_PyCurv Curvature analysis of segmented tomograms
Paper 2021Dimchev_filaments Segmentation of filaments in tomograms
Paper 2022Frangakis_Curvature Use of mean curvature for segmentation and visualization of tomograms
Paper 2022Lamm_MemBrain Membrane segmentation using deep learning
Paper 2023Sazzed_Struwwel Detection and analysis of filament networks
Paper 2023Zeng_AITOM Structural pattern mining by unsupervised deep iterative subtomogram clustering
Paper 2024Gao_DomainFit Protein identification in tomograms by mass spectroscopy, AlphaFold2 and domain fitting
Paper 2024Khosrozadeh_CryoVesNet CryoVesNet: Vesicle segmentation in cryo-electron tomograms
Paper 2024Last_Ais Ais: Interactive segmentation of tomograms
Paper 2024Siggel_ColabSeg Interactive membrane segmentation of tomograms
Paper 2025Chen_GCTransNet GCTransNet: Segmentation of mitochondrias in volume electron microscopy
Paper 2025Morales_Membranes Membrane segmentation with a neural network
Paper 2025Schoennenbeck_CryoVIA CryoVIA: An image analysis toolkit for the quantification of membrane structures

Resolution

Paper 2005Cardone_Resolution Resolution criterion for electron tomography
Chapter 2007Penczek_Resolution Review of resolution criteria for electron tomography
Paper 2015Diebolder_ConicalFSC Conical Fourier Shell Correlation
Paper 2020Vilas_Monotomo Resolution determination in tomograms

Subtomogram analysis

Paper 2000Bohm_Template Macromolecule finding by template matching
Paper 2002Frangakis_Template Macromolecule finding by template matching
Paper 2006Nickell_Review Review of macromolecule finding by template matching (Visual Proteomics)
Paper 2007Best_Review Review of Localization of Protein Complexes by Pattern Recognition
Paper 2007Forster_Review Review of structure determination by subtomogram averaging
Paper 2008Forster_Classification Classification of subtomograms using constrained correlation
Paper 2008Bartesaghi_Classification Classification and averaging of subtomograms
Paper 2008Schmid_Averaging Alignment and averaging of subtomograms
Paper 2010Amat_Averaging Alignment and averaging of subtomograms exploiting thresholding in Fourier space
Paper 2010Yu_PPCA Probabilistic PCA for volume classification
Paper 2013Chen_Averaging Fast alignment of subtomograms using spherical harmonics
Paper 2013Kuybeda_Averaging Alignment and averaging of subtomograms using the nuclear norm of the cluster
Paper 2013Shatsky_Averaging Alignment and averaging of subtomograms with constrained cross-correlation
Paper 2013Yu_Projection Subtomogram averaging by aligning their projections
Paper 2014Chen_Autofocus Subtomogram averaging and classification with special attention to differences
Paper 2014Yu_ReferenceBias Scoring the reference bias
Paper 2014Voortman_LimitingFactors Limiting factors of subtomogram averaging
Paper 2015Bharat_CTFCorrectedSubtomogramAveraging Subtomogram averaging with CTF correction using a Bayesian prior
Paper 2015Yu_ReferenceBias Scoring the reference bias
Paper 2016Bharat_Relion Subtomogram averaging with Relion
Paper 2016Song_MatrixNorm Matrix norm minimization for tomographic reconstruction and alignment
Paper 2017Castano_ParticlePicking Particle picking in tomograms for subtomogram averaging
Paper 2017Frazier_Tomominer TomoMiner a software platform for large-scale subtomogram analysis
Paper 2018Himes_emClarity emClarity for subtomogram averaging
Paper 2018Zhao_Fast Fast alignment and maximum likelihod for subtomogram averaging
Paper 2019Fokine_Enhancement Subtomogram enhancement through the locked self-rotation
Paper 2019Han_Constrained Constrained reconstruction to enhance resolution
Paper 2020Basanta_workflow Workflow for subtomogram averaging
Paper 2020Zeng_GumNet GumNet: Subtomogram averaging using deep learning
Paper 2021Cheng_Native 3D reconstruction only with 0-tilt images
Paper 2021Du_Active Active learning to reduce the need of annotated samples
Paper 2021Harastani_HEMNMA3D HEMNMA-3D: Continuous flexibility analysis of subtomograms using normal modes
Paper 2021Lucas_Cistem Identification of particles in tomograms using Cistem
Paper 2021Moebel_DeepFinder DeepFinder: Identification of particles in tomograms using neural networks
Paper 2021Scaramuzza_Dynamo Subtomogram averaging workflow using Dynamo
Paper 2021Singla_Measures Analysis of different measures to analyze subtomogram clusters
Paper 2021Tegunov_M Image processing workflow for tilt-series (introduction of M)
Conference 2021Zeng_OpenSet Unsupervised open set classification using deep learning
Paper 2022Bandyopadhyay_Adaptation Cryo-Shift: a neural network to bridge the gap between simulated and experimental data
Paper 2022Boehning_CompressedSensing Compressed sensing for subtomogram averaging
Paper 2022Hao_Picking Detection of molecules in tomograms
Paper 2022Harastani_TomoFlow TomoFlow: Continuous flexibility analysis of subtomograms using 3D dense optical flow
Paper 2022Metskas_STA Tricks for a better Subtomogram Averaging
Paper 2022Moebel_unsupervised Unsupervised classification of subtomograms using neural networks
Paper 2022Peters_Feature Feature guided, focused 3D signal permutation for STA
Paper 2023Balyschew_TomoBEAR TomoBEAR: tilt series alignment, reconstruction and subtomogram averaging
Paper 2023Chaillet_Extensive Extensive angular sampling for picking in tomograms
Paper 2023Cheng_GisSPA Detection of protein targets in 0-tilt images
Paper 2023Genthe_PickYolo Subtomogram picking in tomograms
Paper 2023Rice_TomoTwin Subtomogram picking in tomograms
Paper 2024Almira_TTM Theory of the Tensor Template matching for cryoET
Paper 2024Cruz_Template Template matching for cryoET
Paper 2024Huang_MiLoPYP Self-supervised particle localization in tomograms
Paper 2024Jin_Size Subtomogram picking based on size
Paper 2024Karimi_Vesicle Picking of particles embedded in vesicles
Paper 2024Liu_DeepETPicker DeepETPicker, subtomogram picker using deep learning
Paper 2024Powell_TomoDRGN TomoDRGN: continuous heterogeneity in subtomograms
Paper 2024Rangan_CryoDRGNET CryoDRGN-ET: heterogeneity analysis for subtomograms
Paper 2024Wan_StopGap StopGap: program to locate, align and classify subtomograms
Paper 2024Wang_TomoNet Subtomogram picking in flexible lattices
Paper 2025Chaillet_PytomMatchPick pytom-match-pick: particle picking in tomograms
Paper 2025Shah_TomoCPT TomoCPT: particle picking in tomograms
Paper 2025Yan_MPicker Membrane protein picking in electron tomograms
Paper 2025Bartesaghi_StrategiesHet3D Strategies for studying discrete heterogeneity

Single particle tomography

Paper 2012Bartesaghi_Constrained 3D reconstruction by imposing geometrical constraints
Paper 2012Zhang_IPET_FETR FETR: a focused reconstruction algorithm for a single molecule 3D structure determination without any averaging
Paper 2015Galaz_SingleParticleTomography Set of tools for Single Particle Tomography in EMAN2
Paper 2016Galaz_SingleParticleTomography Alignment algorithms and CTF correction

Missing-wedge correction

Paper 2020Kovacs_Filaments Removal of missing wedge artifacts in filamentous tomograms
Paper 2020Moebel_MCMC Missing wedge correction with Monte Carlo Markov Chains
Paper 2020Zhai_LoTTor Missing-wedge correction by LoTTor (Low-Tilt Tomographic 3D Reconstruction for a single molecule structure)
Paper 2023Zhang_REST Missing-wedge correction with neural networks
Paper 2025Kiewisz_ProjectionSynthesis Projection synthesis of electron tomography data using neural networks

Molecular 3D dynamics

Paper 2015Zhang_IPET 3D Structural Dynamics of Macromolecules by individual-particle structures without averaging
Paper 2023Vuillemot_MDTOMO 3D Structural Dynamics of using molecular dynamics and normal modes

Books and reviews

Paper 2000Baumeister_Review Review of electron tomography
Paper 2003Koster_Review Review of electron tomography
Paper 2003Sali_Review Review of electron tomography
Paper 2004Henderson_Review Review of electron microscopy
Paper 2005Lucic_Review Review of electron tomography
Paper 2006Fernandez_Review Review of electron microscopy
Book 2006Frank_TomoBook Electron Tomography
Book 2007McIntosh_Book Cellular Electron Microscopy
Paper 2007Sorzano_Review Review of the image processing steps
Paper 2008Fanelli_ImageFormation Review on the image formation model from the electron waves and open inverse-problems
Paper 2008Fernandez_HPCReview High performance computing in electron cryomicroscopy
Paper 2008Jonic_Review Comparison between electron tomography and single particles
Paper 2012Kudryashev_Review Review of subtomogram averaging
Paper 2013Briggs_Review Review of subtomogram averaging
Paper 2016Beck_Review Review of molecular sociology
Paper 2016Ercius_Review Electron tomography for hard and soft materials research
Paper 2017Galaz_Review Review of single particle tomography
Paper 2017Plitzko_Review Review of electron tomography, FRET and FIB milling
Paper 2019Schur_Review Review of electron tomography and subtomogram averaging
Paper 2021Frangakis_Review Review of tomogram denoising in electron tomography
Paper 2022Forster_Review Review of subtomogram averaging
Paper 2022Liedtke_Review Review of electron tomography in bacterial cell biology
Paper 2022Liu_Review Review of beam image shift and subtomogram averaging
Paper 2023Kim_Review Review of particle picking and volume segmentation
Paper 2023Ochner_Review Review of electron tomography as a way to visualize macromolecules in their native environment
Paper 2023Zhao_Review Review of computational methods for electron tomography
Paper 2023Watson_Review Review of computational methods for electron tomography
Paper 2024Hutchings_Review Review of in situ electron tomography
Paper 2024Schiotz_Review Review of in situ electron tomography
Paper 2025Martinez_Review Review of template matching in electron tomography
Paper 2025Wan_Review Review of sample preparation and data analysis for electron tomography

Software

Paper 1996Kremer_IMOD IMOD
Paper 1996Chen_Priism/IVE Priism/IVE
Paper 1996Frank_Spider Spider
Paper 2004Sorzano_Xmipp Xmipp
Paper 2005Nickell_TOM TOM Toolbox
Paper 2007Messaoudi_TomoJ TomoJ
Paper 2008Heymann_BsoftTomo Bsoft
Paper 2012Zhang IPET FETR IPET
Paper 2015Ding_CaltechTomography Caltech tomography database
Paper 2015Noble_AppionProtomo Batch fiducial-less tilt-series alignment in Appion using Protomo
Paper 2015vanAarle_Astra ASTRA Toolbox
Paper 2016Liu_FullMechTomo Fully mechanically controlled automated electron microscopic tomography
Paper 2017Han_AuTom Software platform for Electron Tomography
Paper 2017Wan_Simulator Electron Tomography Simulator
Paper 2020Martinez-Sanchez_PySeg Template-free membrane proteins detection
Paper 2021Burt_RWD Interoperability between Relion, Warp M, and Dynamo
Paper 2022Jimenez_ScipionTomo Electron tomography within Scipion
Paper 2022Martinez_PyOrg Point pattern analysis for coordinates in tomograms
Paper 2022Ni_EmClarity Processing protocols with EmClarity
Paper 2022Rodriguez_Mepsi Simulation of tomograms with membrane-embedded proteins
Paper 2023Liu_NextPYP NextPYP: a software platform for cryoET
Paper 2023Yee_Ot2Rec Ot2Rec: a software workflow for cryoET
Paper 2024Burt_Relion5 Subtomogram Analysis with RELION 5
Paper 2024Comet_TomoLive TomoLive: Application for cryoET processing in streaming
Paper 2024Gaifas_Blik Blik: Application for cryoET annotation and analysis
Paper 2024Horstmann_PATo PATo: web application for cryoET processing in streaming
Paper 2024Maurer_PyTME PyTME: Template matching for cryoET
Paper 2024Martinez-Sanchez_PolNet PolNet: Simulating the Cellular Context
Paper 2025Harar_FakET FakET: Simulation of electron tomography data using style transfer
Paper 2025Zhan_AITom AITom: AI-guided CryoET Analysis Toolkit

2D Crystals

2D Preprocessing

Paper 1982Saxton_Averaging Radial Correlation Function
Paper 1984Saxton_Distortions 3D Reconstruction of distorted crystals
Paper 1986Henderson_Processing General 2D processing
Paper 2000He_PhaseAlignment Phase consistency and Alignment
Paper 2006Gil_Unbending Crystal unbending

Classification

Paper 1988Frank_Classification MSA and classification in electron crystallography
Paper 1996Fernandez_SOM Classification based on self organizing maps
Paper 1998Sherman_MSA Classification based on MSA

3D Reconstruction

Paper 1985Wang_Solvent Solvent flattening
Paper 1990Henderson_Processing General 3D processing
Paper 2004Marabini_ART Algebraic Reconstruction Technique with blobs for crystals (Xmipp)
Paper 2018Biyani_Badlu Image processing for badly ordered crystals

Books and reviews

Paper 1998Walz_Review Review of 2D crystallography
Paper 1999Glaeser_Review Review of 2D crystallography
Paper 2001Ellis_Review Review of 2D crystallography
Paper 2001Glaeser_Review Review of 2D crystallography
Paper 2004Henderson_Review Review of electron microscopy
Paper 2006Fernandez_Review Review of single particles, electron tomography and crystallography
Paper 2007Sorzano_Review Review of the image processing steps

Software

Paper 1996Crowther_MRC MRC
Paper 2004Sorzano_Xmipp Xmipp
Paper 2007Gipson_2dx 2dx
Paper 2007Heymann_Bsoft Bsoft
Paper 2007Philippsen_IPLT IPLT

3D Crystals - MicroED

Sample Preparation

Paper 2016Shi_Preparation Sample Preparation
Paper 2024Gillman_Cone Eliminating the missing cone

Data Collection

Paper 2014Nannenga_CR Continuous rotation

Data Processing

Paper 2011Wisedchaisri_PhaseExtension Fragment-based phase extension
Paper 2015Hattne_Processing Data Processing
Paper 2016Hattne_Correction Image correction

Software

Paper 2014Iadanza_Processing Data Processing of still diffraction data

Books and Reviews

Paper 2014Nannenga_Review Review of MicroED
Paper 2016Liu_Review Review of MicroED
Paper 2016Rodriguez_Review Review of MicroED

Helical particles

Filament picking

Paper 2021Thurber_Automated Automated picking of filaments
Paper 2023Li_Classification Classification of filament segments using language models
Paper 2025Peng_DiamTR DiamTR: Classification of filaments by diameter

Filament corrections

Paper 1986Egelman_Curved Algorithm for correcting curved filaments
Paper 1988Bluemke_Pitch Algorithm for correcting filaments with different helical pitches
Paper 2006Wang_Pitch Algorithm for correcting filaments with different helical pitches
Paper 2016Yang_Flexible Algorithm for correcting filaments with flexible subunits
Paper 2019Ohashi_SoftBody Algorithm for correcting filaments with flexible helices

Reconstruction

Paper 1952Cochran_Fourier Fourier Bessel transform of filamentous structures
Paper 1958Klug_Fourier Fourier Bessel decomposition of the projection images
Paper 1970DeRosier_Rec Image processing steps towards 3D reconstruction
Paper 1988Stewart_Rec Image processing steps towards 3D reconstruction
Paper 1992Morgan_Rec Image processing steps towards 3D reconstruction
Paper 2005Wang_Iterative Iterative Fourier-Bessel algorithm
Paper 2007Egelman_Iterative Iterative real-space algorithm
Paper 2010Egelman_Pitfalls Pitfalls in helical reconstruction
Paper 2013Desfosses_Spring Helical processing with Spring
Paper 2015Zhang_seam Workflow for the detection of the lattice seam
Paper 2016Rohou_Frealix Helical processing with Frealix
Paper 2017_He Helical processing with Relion
Paper 2019_Pothula 3D Classification through 2D analysis
Paper 2025_Huang Helical parameter estimation by cylinder unrolling
Paper 2025Li_Helicon Helicon: Helical parameter determination and 3D reconstruction from one image

Validation

Paper 2014Egelman_ambiguity How to detect incorrect models
Paper 2025Li_validation Validation of the helical symmetry parameters in EMDB

Books and reviews

Paper 1970DeRosier_Rec Image processing steps towards 3D reconstruction
Paper 1992Morgan_Rec Image processing steps towards 3D reconstruction
Paper 2004Henderson_Review Review of electron microscopy
Paper 2015Sachse_Review Review of the image processing steps in helical particles
Paper 2021Egelman_Review Review of reconstruction problems in helical structures
Paper 2022Wang_Review Review of reconstruction problems in helical structures
Paper 2022Kreutzberger_Review Review of helical reconstruction

Software

Paper 1996Carragher_Phoelix Phoelix
Paper 1996Crowther_MRC MRC
Paper 1996Owen_Brandeis Brandeis

Icosahedral particles

Reconstruction

Paper 1970Crowther_Rec Reconstruction of icosahedral viruses in Fourier space
Paper 1971Crowther_Rec Reconstruction of icosahedral viruses in Fourier space
Paper 1996Fuller_Rec Reconstruction of icosahedral viruses in Fourier space
Paper 1997Thuman_Rec Reconstruction of icosahedral viruses in Fourier space
Paper 2019Goetschius_Asymmetric Approaches to reconstruct asymmetric features in viruses
Paper 2025Chen_Asymmetric Approaches to reconstruct asymmetric features in viruses

Classification

Paper 2005Scheres_Virus Classification of virus capsids in real space

Books and reviews

Paper 1999Baker_Review Review of reconstruction of icosahedral viruses
Paper 1999Conway_Review Review of reconstruction of icosahedral viruses
Paper 2000Thuman_Review Review of reconstruction of icosahedral viruses
Paper 2003Lee_Review Review of reconstruction of icosahedral viruses
Paper 2003Navaza_Review Review of reconstruction of icosahedral viruses
Paper 2006Grunewald_Review Review of reconstruction of icosahedral viruses

Software

Paper 1996Baker_EMPFT EMPFT
Paper 1996Crowther_MRC MRC
Paper 1996Frank_Spider Spider
Paper 1996VanHeel_Imagic Imagic
Paper 2004Sorzano_Xmipp Xmipp
Paper 2013DeLaRosa_Xmipp30 Xmipp 3.0
Paper 2013Morin_Sliz SBGrid SBGrid presentation for eLife

Single molecule 3D structure (non-averaged)

Variety analysis methods

Paper 2024Liu_RNA Variety of RNA tertiary structures
Paper 2024Zhang_Nucleosome Dynamics of nucleosome arrays
Paper 2022Zhang_NucleosomeTrasition Aggregation of nucleosome arrays during phase transition
Paper 2018Lei_DNABennet Flexibility of DNA origami Bennett linkages
Paper 2016Zhang_DNANG Flexibility of DNA-nanogold complex
Paper 2015Zhang_IgG1 Dynamics of IgG1 antibodies

Process methods

Paper 2012Zhang_IPET Forcused electron tomography reconstration (FETR) method
Paper 2016Liu_AutoET Fully Mechanically Controlled Automated Electron Microscopic Tomography
Paper 2018Wu_Contrast An Algorithm for Enhancing the Image Contrast of Electron Tomography
Paper 2020Zhai_LoTToR Missing-wedge correction for the low-tilt tomographic 3D reconstruction of a single molecule

Reviews

Paper 2022Han_Radiation Cryo-ET related radiation-damage parameters for single molecule 3D structure determination

Liquid-cell TEM / in-situ TEM

Paper 2020Ren_LTEM Real-time dynamic imaging of sample in liquid phase
Paper 2023Kong_ViralEntry Molecular imaging of protein, virus and cell samples at room temperature

Databases

Paper 2003Boutselakis_EMSD EMSD database
Paper 2005Heymann_Conventions Conventions for software interoperability
Paper 2005Heymann_Conventions Conventions for software interoperability
Paper 2011Kim_CDDB Conformational Dynamics Data Bank
Paper 2011Lawson_EMDB Electron Microscopy Data Bank
Paper 2013Ison_EDAM EDAM, an ontology of bioinformatics operations
Paper 2016Iudin_EMPIAR EMPIAR raw data database
Paper 2016Patwhardan_EMDB EMDB, PDB, ...
Paper 2017Gore_Validation Validations of PDB submissions
Paper 2017Patwhardan_Trends Trends at EMDB
Paper 2017Shao_PDBQuality Quality metrics in PDB
Paper 2018Tawari_search Search of 3D structures in a database using 2D experimental images
Paper 2018wwwPDB_PDB Review of PDB advances
Paper 2021Nair_PDBe PDBe API
Paper 2022Wang_EMDB Validation analysis of EMDB entries
Paper 2022Westbrook_mmCIF PDBx/mmCIF ecosystem
Paper 2024Kleywegt_ArchivingValidation Community recommendations for archival and validation
Paper 2024Ermel_DataPortal CryoET Data Portal
Paper 2024Vallat_IHMCIF IHMCIF extension of mmCIF for integrative modelling
Paper 2024wwPDB_EMDB Review of EMDB
Blog http://www.mybiosoftware.com Huge list of bioinformatics programs (many of them structural bioinformatics)

Relationship to other structural information sources

Paper 2000Engel_AFM Review of Atomic Force Microscopy
Paper 2001Dimmeler_AFM Constraints from Atomic Force Microscopy
Paper 2003Mobus_EnergyLoss Chemical mapping by energy loss electron tomography
Paper 2004Leapman_EnergyLoss Chemical mapping by energy loss electron tomography
Paper 2004Leapman_Review Review on correlative microscopy
Paper 2005Boudier_EFTETJ Software for Chemical mapping by energy loss electron tomography
Paper 2005Vestergaard_SAXS Example of comparison of 3DEM and Small-angle X-ray scattering
Paper 2007Hamada_SAXS Constraints from Small-angle X-ray scattering
Paper 2013Xu_FRET EM+FRET
Paper 2017Kim_SAXS Compatibility of EM experimental images and SAXS curves
Paper 2018Ando_Correlative Review of correlative microscopy techniques
Paper 2018Sieben_Multicolor Correlative microscopy with superresolution optical images
Paper 2019Huber_EDXS_HAADF Combined reconstruction using EDXS and HAADF data
Paper 2019Jimenez_SAXS Selection of EM initial volumes by SAXS curves
Paper 2022Graziadei_CrossLinking Review on the use of crosslinking mass spectrometry in CryoEM
Paper 2022Klumpe_FIB A modular platform for automated cryo-FIB workflows

X-ray tomography

Paper 2012Oton_ImageFormation Image formation model in X-ray cell microscopy

Mathematical tools necessary

People developing methods

Please, add yourself to this list (due to privacy reasons, please, do not add anyone else to the list without his/her explicit consent). Sort by first name alphabetical order.

Carlos Oscar S. Sorzano: CSIC, Madrid, Spain

Cédric Messaoudi: Institute Curie, Paris, France

Javier Vargas:: CSIC, Madrid, Spain

Joaquín Otón: CSIC, Madrid, Spain

[José Román Bilbao-Castro]: UAL, Almería, Spain; CSIC, Madrid, Spain

[José Miguel de la Rosa Trevín]: Biocomputing Unit CNB-CSIC, Madrid, Spain

Tamir Gonen: Howard Hughes Medical Institute, Ashburn, VA, USA

Tomas Majtner: Biocomputing Unit CNB-CSIC, Madrid, Spain

[Vahid Abrishami]: CSIC, Madrid, Spain

Gang (Gary) Ren: The Molecular Foundry, LBNL, USA

3DEM sites