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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 ===
Line 85: Line 91:
[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 100: Line 106:


[https://va.tech.purdue.edu/cryoVR/index.php Purdue CryoEM Virtual Reality Augmented Training]
[https://va.tech.purdue.edu/cryoVR/index.php Purdue CryoEM Virtual Reality Augmented Training]
[https://www.youtube.com/playlist?list=PLhiuGaXlZZek9D0SZk0OVtTeFVETa1sPG NCCAT Short course on Tomography]
[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 184: 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 384: Line 409:
| [[2018Hettler_Charging]]
| [[2018Hettler_Charging]]
| Charging of carbon thin films
| Charging of carbon thin films
|-
| Paper
| [[2018Koeck_PhaseShift]]
| Design of a phase shift device
|-  
|-  


Line 451: Line 471:
|-  
|-  


|}
| Paper
| [[2021Egerton_Inelastic]]
| PSF of inelastic scattering
|-


=== Collection geometry ===
| Paper
 
| [[2021Himes_Simulation]]
{|
| Simulation of TEM images with special attention to inelastic scattering
 
| Chapter
| [[1980Hoppe_Wedge]]
| Missing wedge
|-  
|-  


| Paper
| Paper
| [[1987Radermacher_RCT]]
| [[2021Glaeser_Fading]]
| Random Conical Tilt and Single axis tilt
| Defocus-dependent Thon-ring fading
|-  
|-  


| Paper
| Paper
| [[1988Radermacher_RCT]]
| [[2021Singer_Wilson]]
| Random Conical Tilt and Single axis tilt
| Detailed analysis of Wilson statistics
|-  
|-  


| Paper
| Paper
| [[1995Penczek_Dual]]
| [[2021Wieferig_Devitrification]]
| Dual axis tomography
| Devitrification reduces beam-induced movement in cryo-EM
|-  
|-  


| Paper
| Paper
| [[1997Mastronarde_Dual]]
| [[2022Bharadwaj_Scattering]]
| Dual axis tomography
| Electron scattering properties and their use for map sharpening
|-  
|-  


| Paper
| Paper
| [[2003Ludtke_FocusPairs]]
| [[2022Heymann_PSSNR]]
| Focus pairs for single particles
| Progressive Spectral Signal-to-Noise Ratio to assess quality and radiation damage
|-  
|-  


| Paper
| Paper
| [[2005Lanzavecchia_Conical]]
| [[2022Dickerson_Inelastic]]
| Conical tomography
| The role of inelastic scattering in thick specimens
|-  
|-  


| Paper
| Paper
| [[2005Zampighi_Conical]]
| [[2022Kulik_TAAM]]
| Conical tomography
| Theoretical 3D electron diffraction electrostatic potential maps of proteins
|-  
|-  


| Paper
| Paper
| [[2006Leschziner_OT]]
| [[2022Ravikumar_SideChains]]
| Orthogonal Tilt
| Comparison of side-chain dispersion in protein structures determined by cryo-EM and X-ray crystallography
|-  
|-  


| Paper
| Paper
| [[2006Messaoudi_Multiple]]
| [[2023Bromberg_Complex]]
| Multiple axis tomography
| CTF and Ewald sphere correction using complex-valued images
|-  
|-  


| Paper
| Paper
| [[2012Kudryashev_FocusPairs]]
| [[2023Heymann_Ewald]]
| Focus pairs tomography
| The Ewald sphere/focus gradient does not limit the resolution of cryoEM reconstructions
|-  
|-  


| Paper
| Paper
| [[2014Hovden_TiltFocus]]
| [[2023McMullan_100kV]]
| Combining tilt series with focus series
| CryoEM at 100kV
|-
 
| Paper
| [[2023Schreiber_charge]]
| Time dynamics of charge buildup
|-
 
| Paper
| [[2023Shi_Compression]]
| Protein compression due to ice formation
|-  
|-  


| Paper
| Paper
| [[2015Sorzano_RandomConicalTilt]]
| [[2024Bochtler_Probes]]
| General formulation of Random Conical Tilt
| X-rays, electrons, and neutrons as probes of atomic matter
|-  
|-  


| Paper
| Paper
| [[2017Hagen_DoseTomography]]
| [[2024Dickerson_magnification]]
| Dose optimization for subtomogram averaging
| Accurate determination of magnification using gold
|-  
|-  


| Paper
| Paper
| [[2017Tan_PreferredViews]]
| [[2024Joosten_Roodmus]]
| Solving preferred views problems through tilting
| Simulation of micrographs of heterogeneous macromolecules
|-  
|-  


| Paper
| Paper
| [[2017Donati_Compressed]]
| [[2024Parkhurst_IceSimulation]]
| Compressed sensing for STEM
| Projections of amorphous ice simulation simulated with Gaussian Random Fields
|-  
|-  


| Paper
| Paper
| [[2018Oveisi_Stereo]]
| [[2024Remis_Damage]]
| Stereo-vision with EM
| Radiation damage revealed by phase plates
|-  
|-  


| Paper
| Paper
| [[2018Cheng_BeamShift]]
| [[2025Dickerson_Damage]]
| Fast image acquisition through beam-shift
| Reduced radiation damage at liquid helium temperature
|-  
|-  


| Paper
| Paper
| [[2019Wu_BeamShiftAndTilt]]
| [[2025Wu_ZeroLossCCCorrected]]
| Fast image acquisition through beam-shift and beam tilt control
| Imaging with chromatic aberration correction and zero loss electrons
|-  
|-  


|}
|}


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


{|
{|
| Chapter
| [[1980Hoppe_Wedge]]
| Missing wedge
|-


| Paper
| Paper
| [[1982Dubochet_Sample]]
| [[1987Radermacher_RCT]]
| Vitreous ice
| Random Conical Tilt and Single axis tilt
|-  
|-  


| Paper
| Paper
| [[1986Lepault_Sample]]
| [[1988Radermacher_RCT]]
| Fast freezing
| Random Conical Tilt and Single axis tilt
|-  
|-  


| Paper
| Paper
| [[1995Dubochet_Sample]]
| [[1995Penczek_Dual]]
| High-pressure freezing
| Dual axis tomography
|-  
|-  


| Paper
| Paper
| [[1995VanMarle_Sample]]
| [[1997Mastronarde_Dual]]
| Sample damages in resin
| Dual axis tomography
|-  
|-  


| Paper
| Paper
| [[1998Adrian_Sample]]
| [[2003Ludtke_FocusPairs]]
| Cryo negative staining
| Focus pairs for single particles
|-  
|-  


| Paper
| Paper
| [[2002DeCarlo_Damage]]
| [[2005Lanzavecchia_Conical]]
| Radiation damage in cryonegative staining
| Conical tomography
|-  
|-  


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


| Paper
| Paper
| [[2004AlAmoudi_Sample]]
| [[2006Leschziner_OT]]
| CEMOVIS
| Orthogonal Tilt
|-  
|-  


| Paper
| Paper
| [[2008Studer_Sample]]
| [[2006Messaoudi_Multiple]]
| Review on high pressure freezing
| Multiple axis tomography
|-  
|-  


| Paper
| Paper
| [[2009Pierson_Sample]]
| [[2012Kudryashev_FocusPairs]]
| Review on sample preparation for electron tomography
| Focus pairs tomography
|-  
|-  


| Paper
| Paper
| [[2010Zhang_OpNS]]
| [[2014Hovden_TiltFocus]]
| Optimized negative staining (OpNS) for small protein and lipoprotein imaging
| Combining tilt series with focus series
|-  
|-  


| Paper
| Paper
| [[2012Zhang_Cryo-PS]]
| [[2015Sorzano_RandomConicalTilt]]
| Cryo-positive staining (Cryo-PS)
| General formulation of Random Conical Tilt
|-  
|-  


| Paper
| Paper
| [[2014Russo_GoldGrids]]
| [[2017Hagen_DoseTomography]]
| Gold grids for single particles
| Dose optimization for subtomogram averaging
|-  
|-  


| Paper
| Paper
| [[2015Cabra_Sample]]
| [[2017Tan_PreferredViews]]
| Review on sample preparation for single particles with videos
| Solving preferred views problems through tilting
|-  
|-  


| Paper
| Paper
| [[2015Chari_ProteoPlex]]
| [[2017Donati_Compressed]]
| Fast evaluation of the structural stability
| Compressed sensing for STEM
|-  
|-  


| Paper
| Paper
| [[2016Passmore_Review]]
| [[2018Oveisi_Stereo]]
| Tutorial chapter on sample preparation
| Stereo-vision with EM
|-  
|-  


| Paper
| Paper
| [[2016Razinkov_Vitrification]]
| [[2018Cheng_BeamShift]]
| New vitrification method
| Fast image acquisition through beam-shift
|-  
|-  


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


| Paper
| Paper
| [[2016Thompson_Sample]]
| [[2023Seifer_RevisedSaxton]]
| Review on sample preparation for EM
| Revised Saxton geometry for tilt series acquisition
|-  
|-  
|}
=== Sample preparation ===
{|


| Paper
| Paper
| [[2017Arnold_BlottingFree]]
| [[1982Dubochet_Sample]]
| Blotting-free preparation
| Vitreous ice
|-
|-  


| Paper
| Paper
| [[2017Earl_review]]
| [[1986Lepault_Sample]]
| Review of sample preparation
| Fast freezing
|-
|-  


| Paper
| Paper
| [[2017Feng_SprayingPlunging]]
| [[1995Dubochet_Sample]]
| Spraying plunging
| High-pressure freezing
|-
|-  


| Paper
| Paper
| [[2017He_FIB]]
| [[1995VanMarle_Sample]]
| Cryo FIB lamella for TEM
| Sample damages in resin
|-
|-  


| Paper
| Paper
| [[2017Peitsch_Sample]]
| [[1998Adrian_Sample]]
| iMEM: Isolation of Plasma Membrane for Cryoelectron Microscopy
| Cryo negative staining
|-
|-  


| Paper
| Paper
| [[2017Scapin_Storage]]
| [[2002DeCarlo_Damage]]
| Cryo storage of samples
| Radiation damage in cryonegative staining
|-
|-  


| Paper
| Paper
| [[2017Schaffer_FocusedIonBeam]]
| [[2002Hsieh_Sample]]
| Focused Ion Beam sample preparation for membrane proteins
| Cryofixation
|-
|-  


| Paper
| Paper
| [[2017Scherr_HydrogelNanomembranes]]
| [[2004AlAmoudi_Sample]]
| Sample preparation for membrane proteins
| CEMOVIS
|-
|-  


| Paper
| Paper
| [[2018Anderson_CLEM]]
| [[2008Studer_Sample]]
| Correlated light and EM
| Review on high pressure freezing
|-
|-  


| Paper
| Paper
| [[2018Arnold_Review]]
| [[2009Pierson_Sample]]
| Review on sample preparation with special emphasis on microfluidic approaches
| Review on sample preparation for electron tomography
|-
|-  


| Paper
| Paper
| [[2018Dandey_Spotiton]]
| [[2010Zhang_OpNS]]
| Spotiton, a device for vitrification
| Optimized negative staining (OpNS) for small protein and lipoprotein imaging
|-
|-  


| Paper
| Paper
| [[2018Gewering_Detergents]]
| [[2012Zhang_Cryo-PS]]
| Detergent background in negative stain
| Cryo-positive staining (Cryo-PS)
|-
|-  


| Paper
| Paper
| [[2018Li_CLEM]]
| [[2014Russo_GoldGrids]]
| Correlated light and EM
| Gold grids for single particles
|-
|-  


| Paper
| Paper
| [[2018Noble_Reducing]]
| [[2015Cabra_Sample]]
| Reducing particle adsorption
| 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
| [[2020Fassler_Printing]]
| [[2017Feng_SprayingPlunging]]
| 3D printed cell culture grid holder
| Spraying plunging
|-
|-


| Paper
| Paper
| [[2020Klebl_Deposition]]
| [[2017He_FIB]]
| Sample deposition onto CryoEM grids: sprays and jets
| Cryo FIB lamella for TEM
|-
|-


| Paper
| Paper
| [[2020Maeots_TimeResolved]]
| [[2017Peitsch_Sample]]
| Time resolved CryoEM by microfluidics
| iMEM: Isolation of Plasma Membrane for Cryoelectron Microscopy
|-
|-


| Paper
| Paper
| [[2020Yoder_TimeResolved]]
| [[2017Scapin_Storage]]
| Time resolved CryoEM by light estimulation
| Cryo storage of samples
|-
|-


|}
| Paper
| [[2017Schaffer_FocusedIonBeam]]
| Focused Ion Beam sample preparation for membrane proteins
|-


=== Automated data collection ===
| Paper
 
| [[2017Scherr_HydrogelNanomembranes]]
{|
| Sample preparation for membrane proteins
|-


| Paper
| Paper
| [[1992Dierksen_Automatic]]
| [[2018Anderson_CLEM]]
| Automated data collection
| Correlated light and EM
|-  
|-


| Paper
| Paper
| [[1992Koster_Automatic]]
| [[2018Arnold_Review]]
| Automated data collection
| Review on sample preparation with special emphasis on microfluidic approaches
|-  
|-


| Paper
| Paper
| [[1996Fung_Automatic]]
| [[2018Ashtiani_femtolitre]]
| Automated data collection for tomography
| Delivery of femtolitre droplets using surface acoustic wave based atomisation for cryo-EM grid preparation
|-  
|-


| Paper
| Paper
| [[2001Zhang_Automatic]]
| [[2018Dandey_Spotiton]]
| Automated data collection: AutoEM
| Spotiton, a device for vitrification
|-  
|-


| Paper
| Paper
| [[2003Ziese_Automatic]]
| [[2018Gewering_Detergents]]
| Automated autofocusing
| Detergent background in negative stain
|-  
|-


| Paper
| Paper
| [[2004Potter_Automatic]]
| [[2018Li_CLEM]]
| Automated sample loading
| Correlated light and EM
|-  
|-


| Paper
| Paper
| [[2004Zheng_Automatic]]
| [[2018Noble_Reducing]]
| Automated data collection
| Reducing particle adsorption
|-  
|-


| Paper
| Paper
| [[2005Lei_Automatic]]
| [[2018Palovcak_Graphene]]
| Automated data collection: AutoEM
| Preparation of graphene-oxide cryo-EM grids
|-  
|-


| Paper
| Paper
| [[2005Suloway_Automatic]]
| [[2018Rice_Ice]]
| Automated data collection: Leginon
| Routine determination of ice thickness
|-  
|-


| Paper
| Paper
| [[2007Yoshioka_RCT]]
| [[2018Schmidli_Miniaturized]]
| Automated Random Conical Tilt
| Protein isolation and sample preparation
|-  
|-


| Paper
| Paper
| [[2011Korinek_TOM2]]
| [[2018Wei_Grids]]
| Automated acquisition with TOM2
| "Self-wicking" nanowire grids
|-  
|-


| Paper
| Paper
| [[2015Li_UCSFImage]]
| [[2019DImprima_Denaturation]]
| Automated acquisition with UCSFImage
| Protein denaturation at the air-water interface and how to prevent it
|-  
|-


| Paper
| Paper
| [[2016Gil_Fuzzy]]
| [[2019Rubinstein_ultrasonic]]
| Real time decisions during acquisition with neuro-fuzzy method
| Ultrasonic specimen preparation device
|-  
|-


| Paper
| Paper
| [[2016Liu_TiltControl]]
| [[2019Song_FalconIII]]
| Accurate control of the tilt angle for electron tomography
| Comparison of the modes of Falcon III
|-  
|-


| Paper
| Paper
| [[2016Vargas_FoilHole]]
| [[2020Cianfrocco_Wrong]]
| Determination of image quality at low magnification
| What could go wrong?
|-  
|-


| Paper
| Paper
| [[2017Alewijnse_Best]]
| [[2020Egelman_Ice]]
| Best practices for managing large CryoEM facilities
| Problems with the ice
|-  
|-


| Paper
| Paper
| [[2017Biyani_Focus]]
| [[2020Fassler_Printing]]
| Automatic processing of micrographs
| 3D printed cell culture grid holder
|-  
|-


| Paper
| Paper
| [[2018Gomez_Facilities]]
| [[2020Klebl_Deposition]]
| Use of Scipion at facilities
| Sample deposition onto CryoEM grids: sprays and jets
|-  
|-


| Paper
| Paper
| [[2018Sorzano_Gain]]
| [[2020Maeots_TimeResolved]]
| Estimation of the DDD camera gain or residual gain
| Time resolved CryoEM by microfluidics
|-  
|-


| Paper
| Paper
| [[2019Chreifi_TiltSeries]]
| [[2020Tan_ThroughGrid]]
| Rapid tilt-series acquisition for electron cryotomography
| Through-grid wicking enables high-speed 1 cryoEM specimen preparation
|-  
|-


| Paper
| Paper
| [[2019Eng_ImageCompression]]
| [[2020Yoder_TimeResolved]]
| 3D Reconstruction from compressed images
| Time resolved CryoEM by light estimulation
|-  
|-


| Paper
| Paper
| [[2019Hamaguchi_CryoARM]]
| [[2020Zachs_FIB]]
| CryoARM data acquisition
| Automation for FIB milling
|-  
|-


| Paper
| Paper
| [[2019Maluenda_Scipion]]
| [[2021Bieber_FIBET]]
| Automated workflow processing for facilities
| Sample preparation for correlative FIB milling and CryoET
|-  
|-


| Paper
| Paper
| [[2019Schorb_ET]]
| [[2021Budell_TimeResolved]]
| Automated acquisition in Electron Tomography
| Time resolved CryoEM with Spotiton
|-  
|-


| Paper
| Paper
| [[2019Tegunov_Warp]]
| [[2021Casasanta_Microchip]]
| Automatic micrograph processing with Warp
| Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy
|-  
|-
 
| Paper
| [[2021Frechard_Preparation]]
| Optimization of Sample Preparation
|-


| Paper
| Paper
| [[2019Thompson_Protocol]]
| [[2021Engstrom_Nitrogen]]
| Protocol for EM acquisition
| Samples vitrified in boiling nitrogen
|-  
|-


| Paper
| Paper
| [[2020Baxa_Facility]]
| [[2021Jagota_GoldNanoparticles]]
| Operational workflow in a facility
| Gold nanoparticles to assess flexibility
|-  
|-


| Paper
| Paper
| [[2020Guo_EER]]
| [[2021Jiang_MoAu]]
| Electron event representation for acquisition
| Holey Gold Films on Molybdenum Grids
|-  
|-


| Paper
| Paper
| [[2020Li_Workflow]]
| [[2021Jonaid_Liquid]]
| Workflow for automatic reconstruction
| Liquid phase EM
|-  
|-


| Paper
| Paper
| [[2020Sader_Facility]]
| [[2021Ki_Conformational]]
| Microscope installation and operation in a facility
| Conformational Distribution of a Small Protein with Nanoparticle-Aided CryoEM
|-  
|-


| Paper
| Paper
| [[2020Schenk_CryoFlare]]
| [[2021Li_detergents]]
| CryoFlare, automatic data acquisition
| The effect of detergents on preferential orientations
|-  
|-


| Paper
| Paper
| [[2020Weis_Acquisition]]
| [[2021Voss_Melting]]
| Suggestions for high-quality and high-throughput acquisition
| Rapid melting and revitrification as an approach to microsecond time-resolved cryoEM
|-  
|-


|}
| Paper
| [[2021Zhang_Pegylation]]
| Improving particle quality in cryo-EM by PEGylation
|-


== Single particles ==
| Paper
| [[2022Chen_Detergents]]
| Role of detergents in the air-water interface
|-


=== Automatic particle picking ===
| 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
| Paper
| [[1982VanHeel_Detection]]
| [[2022Russo_Review]]
| Detection of particles in micrographs
| Review of sample preparation issues
|-  
|-


| Paper
| Paper
| [[2001Nicholson_Review]]
| [[2022Scher_FIB]]
| Review on automatic particle picking
| Sample preparation for FIB-SEM and Correlative microscopy
|-  
|-


| Paper
| Paper
| [[2001Zhu_Filaments]]
| [[2023Basanta_Graphene]]
| Automatic identification of filaments in micrographs
| Fabrication of Monolayer Graphene-Coated Grids
|-  
|-


| Paper
| Paper
| [[2004Sigworth_Detection]]
| [[2023Grassetti_Graphene]]
| Classical detection theory and the cryo-EM particle selection problem
| Improving graphane monolayer sample preparation
|-  
|-


| Paper
| Paper
| [[2004Volkmann_ParticlePicking]]
| [[2023Han_Sample]]
| An approach to automated particle picking from electron micrographs based on reduced representation templates
| Challenges in making ideal cryo-EM samples
|-  
|-


| Paper
| Paper
| [[2004Wong_ParticlePicking]]
| [[2023Liu_AirWater]]
| Model-based particle picking for cryo-electron microscopy
| Review on sample preparation techniques to deal with the air-water interface
|-  
|-


| Paper
| Paper
| [[2004Zhu_Review]]
| [[2023Langeberg_RNAScaffold]]
| Review on automatic particle picking
| RNA scaffolds for small proteins
|-  
|-


| Paper
| Paper
| [[2007Chen_Signature]]
| [[2023Neselu_IceThickness]]
| Automatic particle picking program: Signature
| Effect of ice thickness on resolution
|-  
|-


| Paper
| [[2023Torino_TimeResolved]]
| Device for the preparation of time-resolved CryoEM experiments
|-


| Paper
| Paper
| [[2007Woolford_SwarmPS]]
| [[2023Venien_Membrane]]
| Automatic particle picking with several criteria, implemented in EMAN Boxer
| Review on the preparation of membrane proteins
|-  
|-


| Paper
| Paper
| [[2009Sorzano_MachineLearning]]
| [[2023Zheng_Ultraflat]]
| Automatic particle picking based on machine learning of rotational invariants
| Uniform thin ice on ultraflat graphene grids
|-  
|-


| Paper
| Paper
| [[2011Arbelaez_Comparison]]
| [[2024Esfahani_SPOTRASTR]]
| Evaluation of the performance of software for automated particle-boxing
| SPOT-RASTR: A sample preparation technique that overcomes preferred orientations
|-
|-


| Paper
| Paper
| [[2013Abrishami_MachineLearning]]
| [[2024Abe_LEA]]
| A pattern matching approach to the automatic selection of particles from low-contrast electron micrographs
| LEA proteins to reduce the air-water interface interaction
|-
|-


| Paper
| Paper
| [[2013Hauer_2013]]
| [[2024Bhattacharjee_TimeResolved]]
| Automatic tilt pair detection in Random Conical Tilt
| Time-resolved cryoEM with a microfluidic device
|-
|-


| Paper
| Paper
| [[2013Hoang_ParallelGPUPicking]]
| [[2024Harley_40]]
| Parallel GPU-accelerated particle picking
| Pluge freezing over 40 degrees
|-
|-


| Paper
| Paper
| [[2013Shatsky_ParticlePicking]]
| [[2024Henderikx_Vitrojet]]
| Automated particle correspondence and accurate tilt-axis detection in tilted-image pairs
| Use cases of Vitrojet
|-
|-


| Paper
| Paper
| [[2013Vargas_ParticleQuality]]
| [[2024Hsieh_MinIce]]
| Automatic determination of particle quality
| Minimization of the ice contamination for cryoET
|-  
|-


| Paper
| Paper
| [[2014Langlois_ParticlePicking]]
| [[2024Liu_Graphene]]
| Automatic particle picking
| Review of the use of graphene for grid preparation
|-  
|-


| Paper
| Paper
| [[2015Scheres_SemiAutoPicking]]
| [[2024Mueller_Facility]]
| Semi-automated selection of cryo-EM particles
| Sample workflow at the facility
|-  
|-


| Paper
| Paper
| [[2016Vilas_AutomaticTilt]]
| [[2024Tuijtel_Lamellae]]
| Automatic identification of image pairs in untilted-tilted micrograph pairs
| Optimizing lamellae for subtomogram averaging
|-  
|-


| Paper
| Paper
| [[2016Wang_DeepPicker]]
| [[2024Yadav_Orientation]]
| A deep learning approach for fully automated particle picking
| Experimental factors affecting orientation distribution
|-  
|-


| Paper
| Paper
| [[2017Zhu_DeepEM]]
| [[2025Chen_Detergent]]
| Deep learning approach to picking
| Review on the use of detergents to extract membran proteins and their effects on CryoEM
|-  
|-


| Paper
| Paper
| [[2018Huber_Helices]]
| [[2025Elad_Review]]
| Automated tracing of helices
| Review of sample preparation for in situ protein visualization
|-  
|-


| Paper
| Paper
| [[2018Heimowitz_ApplePicker]]
| [[2025Grant_Nanodisc]]
| Automated particle picking
| Review on the use of nanodiscs for sample preparation
|-  
|-


| Paper
| Paper
| [[2018Sanchez_DeepConsensus]]
| [[2025Gusach_Diffusion]]
| Deep learning consensus of multiple automatic pickers
| Sample vitrification faster than protein diffusion
|-  
|-


| Paper
| Paper
| [[2019Alazzawi_Clustering]]
| [[2025Haynes_OptimalIce]]
| Use of clustering algorithms to find particles in micrographs
| Vitrification conditions for optimal ice thickness
|-  
|-


| Paper
| Paper
| [[2019Bepler_Topaz]]
| [[2025Sun_PlasmaMembranes]]
| Deep learning for particle picking
| Sample preparation pipeline for plasma membrane analysis by CryoET
|-  
|-


| Paper
|}
| [[2019Carrasco_IP]]
| Use of standard image processing for particle picking
|-


| Conference
=== Automated data collection ===
| [[2019Li_Deep]]
 
| Deep learning for particle picking without box size
{|
 
| Paper
| [[1992Dierksen_Automatic]]
| Automated data collection
|-  
|-  


| Paper
| Paper
| [[2019Wagner_Cryolo]]
| [[1992Koster_Automatic]]
| Deep learning for particle picking
| Automated data collection
|-  
|-  


| Paper
| Paper
| [[2019Wang_Biobjective]]
| [[1996Fung_Automatic]]
| Biobjective function for robust signal detection
| Automated data collection for tomography
|-  
|-  


| Paper
| Paper
| [[2019Zhang_Pixer]]
| [[2001Zhang_Automatic]]
| Deep learning for particle picking
| Automated data collection: AutoEM
|-  
|-  


| Paper
| Paper
| [[2020Sanchez_Cleaner]]
| [[2003Ziese_Automatic]]
| Deep learning for removing particles from the carbon edges, aggregations, contaminations, ...
| Automated autofocusing
|-  
|-  
|}
=== 2D Preprocessing ===
{|


| Paper
| Paper
| [[1978Carrascosa_matching]]
| [[2004Potter_Automatic]]
| Gray values matching by linear transformations
| Automated sample loading
|-  
|-  


| Paper
| Paper
| [[2003Rosenthal_DPR]]
| [[2004Zheng_Automatic]]
| Contrast enhancement through DPR
| Automated data collection
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Normalization]]
| [[2005Lei_Automatic]]
| Normalization procedures and their statistical properties.
| Automated data collection: AutoEM
|-  
|-  


| Paper
| Paper
| [[2006Sorzano_Denoising]]
| [[2005Suloway_Automatic]]
| Strong denoising in wavelet space
| Automated data collection: Leginon
|-  
|-  


| Conference
| Paper
| [[2009Sorzano_Downsampling]]
| [[2007Yoshioka_RCT]]
| Differences between the different downsampling schemes
| Automated Random Conical Tilt
|-  
|-  


| Paper
| Paper
| [[2012Brilot_Movies]]
| [[2011Korinek_TOM2]]
| Alignment of beam induced motion in direct detectors
| Automated acquisition with TOM2
|-  
|-  


| Paper
| Paper
| [[2012Campbell_Movies]]
| [[2015Li_UCSFImage]]
| Alignment of beam induced motion in direct detectors
| Automated acquisition with UCSFImage
|-  
|-  


| Paper
| Paper
| [[2012Zhao_Denoising]]
| [[2016Gil_Fuzzy]]
| Denoising using an invariant Fourier-Bessel eigenspace
| Real time decisions during acquisition with neuro-fuzzy method
|-  
|-  


| Paper
| Paper
| [[2013Norousi_Screening]]
| [[2016Liu_TiltControl]]
| Screening particles to identify outliers
| Accurate control of the tilt angle for electron tomography
|-  
|-  


| Paper
| Paper
| [[2013Bai_ElectronCounting]]
| [[2016Vargas_FoilHole]]
| Electron counting and beam induced motion correction
| Determination of image quality at low magnification
|-  
|-  


| Paper
| Paper
| [[2013Li_ElectronCounting]]
| [[2017Alewijnse_Best]]
| Electron counting and beam induced motion correction
| Best practices for managing large CryoEM facilities
|-  
|-  


| Paper
| Paper
| [[2013Shigematsu_Movies]]
| [[2017Biyani_Focus]]
| Drift correction for movies considering dark field
| Automatic processing of micrographs
|-  
|-  


| Paper
| Paper
| [[2013Vargas_ParticleQuality]]
| [[2018Gomez_Facilities]]
| Automatic determination of particle quality
| Use of Scipion at facilities
|-  
|-  


| Paper
| Paper
| [[2014Scheres_Movies]]
| [[2018Sorzano_Gain]]
| Beam induced motion correction
| Estimation of the DDD camera gain or residual gain
|-  
|-  


| Paper
| Paper
| [[2015Abrishami_Movies]]
| [[2019Chreifi_TiltSeries]]
| Alignment of direct detection device micrographs
| Rapid tilt-series acquisition for electron cryotomography
|-  
|-  


| Paper
| Paper
| [[2015Grant_Anisotropic]]
| [[2019Eng_ImageCompression]]
| Automatic estimation and correction of anisotropic magnification
| 3D Reconstruction from compressed images
|-  
|-  


| Paper
| Paper
| [[2015Grant_OptimalExposure]]
| [[2019Eisenstein_FISE]]
| Filter movies according to the radiation damage
| Improved applicability and robustness of fast cryo-electron tomography data acquisition
|-  
|-  


| Paper
| Paper
| [[2015Rubinstein_Alignment]]
| [[2019Hamaguchi_CryoARM]]
| Frame alignment at the level of particle
| CryoARM data acquisition
|-  
|-  


| Paper
| Paper
| [[2015Spear_DoseCompensation]]
| [[2019Maluenda_Scipion]]
| Effect of dose compensation on resolution
| Automated workflow processing for facilities
|-  
|-  


| Paper
| Paper
| [[2015Zhao_AnisotropicMagnification]]
| [[2019Schorb_ET]]
| Correction of anisotropic magnification
| Automated acquisition in Electron Tomography
|-  
|-  


| Conference
| Paper
| [[2016Bajic_Denoising]]
| [[2019Tegunov_Warp]]
| Denoising and deconvolution of micrographs
| Automatic micrograph processing with Warp
|-  
|-  


| Paper
| Paper
| [[2016Jensen_RemovalVesicles]]
| [[2019Thompson_Protocol]]
| Removal of vesicles in membrane proteins
| Protocol for EM acquisition
|-  
|-  


| Paper
| Paper
| [[2016Bhamre_Denoising]]
| [[2020Baxa_Facility]]
| Denoising by 2D covariance estimation
| Operational workflow in a facility
|-  
|-  


| Paper
| Paper
| [[2017Berndsen_EMPH]]
| [[2020Guo_EER]]
| Automated hole masking algorithm
| Electron event representation for acquisition
|-  
|-  


| Paper
| Paper
| [[2017McLeod_Zorro]]
| [[2020Li_Workflow]]
| Movie alignment by Zorro
| Workflow for automatic reconstruction
|-  
|-  


| Paper
| Paper
| [[2017Zheng_MotionCorr2]]
| [[2020Maruthi_Automatic]]
| Movie alignment by MotionCorr2
| Evaluation of MicAssess and CryoAssess
|-  
|-  


| Paper
| Paper
| [[2018Ouyang_Denoising]]
| [[2020Sader_Facility]]
| Denoising based on geodesic distance
| Microscope installation and operation in a facility
|-  
|-  


| Paper
| Paper
| [[2018Wu_ContrastEnhancement]]
| [[2020Schenk_CryoFlare]]
| Contrast enhancement
| CryoFlare, automatic data acquisition
|-  
|-  


| Paper
| Paper
| [[2019Zivanov_BayesianBIM]]
| [[2020Stabrin_Transphire]]
| Bayesian correction of beam induced movement
| TranSPHIRE: Automated and feedback-optimized on-the-fly processing for cryo-EM
|-  
|-  


| Paper
| Paper
| [[2020Chung_Prepro]]
| [[2020Yokoyama_Good]]
| Preprocessing of particles for better alignment
| Deep learning for determining good regions in a grid
|-
 
 
| Paper
| [[2020Weis_Acquisition]]
| Suggestions for high-quality and high-throughput acquisition
|-  
|-  


| Conference
| Paper
| [[2020Huang_SuperResolution]]
| [[2021Feathers_Superresolution]]
| Deep learning superresolution combination of frames
| Effects of superresolution and magnification on final resolution
|-  
|-  


| Paper
| Paper
| [[2020Palovcak_noise2noise]]
| [[2021Bouvette_Bisect]]
| Noise2noise denoising of micrographs
| Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography
|-  
|-  


| Paper
| Paper
| [[2020Strelak_FlexAlign]]
| [[2021Chreifi_FISE]]
| Continuous deformation model for aligning movie frames
| Rapid tilt-series method for cryo-electron tomography: Characterizing stage behavior during FISE acquisition
|-  
|-  


|}
| Paper
| [[2021Danev_Eval]]
| Evaluation of different automatic acquisition schemes
|-


=== 2D Alignment ===
| Paper
 
| [[2021Efremov_ComaCorrected]]
{|
| Coma-corrected rapid single-particle cryo-EM data collection on the CRYO ARM 300
|-


| Paper
| Paper
| [[1981Frank_Averaging]]
| [[2021Herzik_Setup]]
| 2D averaging and phase residual
| Setup for parallel illumination
|-  
|-  


| Paper
| Paper
| [[1982Saxton_Averaging]]
| [[2021Kayama_Multipurpose]]
| 2D averaging using correlation
| Below 3 Å structure of apoferritin using a multipurpose TEM with a side entry cryoholder
|-  
|-  


| Paper
| Paper
| [[1998Sigworth_ML2D]]
| [[2021Lane_NegativeBias]]
| Maximum likelihood alignment in 2D
| Negative potential bias for faster imaging
|-  
|-  


| Paper
| Paper
| [[2003Cong_FRM2D]]
| [[2021Rheinberger_IceThickness]]
| Fast Rotational Matching in 2D
| Scripts to measure ice thickness
|-  
|-  


| Paper
| Paper
| [[2005Cong_FRM2D]]
| [[2021Yang_CRIM]]
| Fast Rotational Matching in 2D introduced in a 3D Alignment algorithm
| Computer readable image markers (CRIM) for correlative microscopy
|-  
|-  


| Paper
| Paper
| [[2005Scheres_ML2D]]
| [[2021Weis_Strategies]]
| Multireference alignment and classification in 2D
| Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition
|-  
|-  


| Paper
| Paper
| [[2016Aguerrebere_Limits]]
| [[2021Wypych_gP2S]]
| Fundamental limits of 2D translational alignment
| LIMS of microscope sessions
|-  
|-  


| Paper
| Paper
| [[2010Sorzano_CL2D]]
| [[2021Yang_CLEM]]
| Multireference alignment and classification in 2D
| Automated correlative microscopy
|-  
|-  


| Conference
| Paper
| [[2017Anoshina_Correlation]]
| [[2021Yonekura_Hole]]
| New correlation measure for aligning images
| Automated hole detection using YOLO
|-  
|-  


| Paper
| Paper
| [[2019Radermacher_Correlation]]
| [[2022Bepler_Smart]]
| On the properties of cross correlation for the alignment of images
| Smart data collection
|-  
|-  


| Paper
| Paper
| [[2020Lederman_representation]]
| [[2022Bouvette_SmartScope]]
| A representation theory perspective of alignment and classification
| SmartScope
|-  
|-  


| Paper
| Paper
| [[2020Marshall_Invariants]]
| [[2022Flutty_bits]]
| Recovery of an image from its invariants
| Bit-precision for SPA and ET
|-  
|-  
|}
=== 2D Classification and clustering ===
{|


| Paper
| Paper
| [[1981VanHeel_MSA]]
| [[2022Hagen_Screening]]
| Multivariate Statistical Analysis
| Screening of ice thickness using energy filter-based plasmon imaging
|-  
|-  


| Paper
| Paper
| [[1984VanHeel_MSA]]
| [[2022Hohle_Ice]]
| Multivariate Statistical Analysis
| Screening of ice thickness using interferometry
|-  
|-  


| Paper
| Paper
| [[2005Scheres_ML2D]]
| [[2022Peck_200]]
| Multireference alignment and classification in 2D
| High-speed high-resolution data collection on a 200 keV cryo-TEM
|-  
|-  


| Paper
| Paper
| [[2010Sorzano_CL2D]]
| [[2022Peck_Montage]]
| Multireference alignment and classification in 2D
| Montage electron tomography
|-  
|-  


| Paper
| Paper
| [[2011Singer_DiffusionMaps]]
| [[2022Zhu_ElectronCounting]]
| Classification in 2D based on graph analysis of the projections
| New algorithm for electron counting at the microscope
|-  
|-  


| Paper
| Paper
| [[2012Yang_ISAC]]
| [[2023Cheng_Leginon]]
| Iterative Stable Alignment and clustering
| Smart data collection with Leginon
|-  
|-  


| Paper
| Paper
| [[2014Sorzano_Outlier]]
| [[2023Kim_Ptolemy]]
| Outlier detection in 2D classifications.
| Smart data collection with Ptolemy
|-  
|-  


| Paper
| Paper
| [[2014Zhao_Aspire]]
| [[2023Last_Ice]]
| Fast classification based on rotational invariants and vector diffusion maps
| Measuring the ice thickness with an optical device and a neural network
|-  
|-  


| Paper
| Paper
| [[2015Huang_Robust]]
| [[2023Mendez_Pipelines]]
| Robust w-estimators of 2D classes
| Evaluation of pipelines for stream processing
|-  
|-  


| Paper
| Paper
| [[2016Kimanius_Accelerated]]
| [[2024Bobe_Calibration]]
| GPU Accelerated image classification and high-resolution refinement
| CryoEM Calibration workflow
|-  
|-  


| Paper
| Paper
| [[2016Reboul_Stochastic]]
| [[2024Eisenstein_SPACETomo]]
| Stochastic Hill Climbing for calculating 2D classes
| Automated acquisition of tilt series
|-  
|-  


| Conference
| Conference
| [[2017Bhamre_Mahalanobis]]
| [[2024Fan_RL]]
| 2D classification using Mahalanobis distance
| Reinforcement learning to optimize the microscope use
|-  
|-  


| Paper
| Paper
| [[2017Wu_GTM]]
| [[2024Hatton_EMinsight]]
| 2D classification using Generative Topographic Mapping
| EMinsight: a tool to capture cryoEM microscope configuration and experimental outcomes for analysis and deposition
|-  
|-  


| Conference
| Paper
| [[2018Boumal_SinglePass]]
| [[2024Xu_Miffi]]
| Single pass classification  
| Miffi: automatic classification of micrographs
|-  
|-  


| Conference
| Paper
| [[2018Shuo_Network]]
| [[2025Bhandari_Fast]]
| 2D Clustering by network metrics
| Data acquisition in EPU Fast mode
|-  
|-  


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


|}
== Single particles ==


=== 3D Alignment ===
=== Automatic particle picking ===


{|
{|


| Paper
| Paper
| [[1980Kam_AutoCorrelation]]
| [[1982VanHeel_Detection]]
| Reconstruction without angular assignment from autocorrelation function (reference free)
| Detection of particles in micrographs
|-  
|-  


| Paper
| Paper
| [[1986Goncharov_CommonLines]]
| [[2001Nicholson_Review]]
| Angular assignment using common lines (reference free)
| Review on automatic particle picking
|-  
|-  


| Paper
| Paper
| [[1987VanHeel_CommonLines]]
| [[2001Zhu_Filaments]]
| Angular assignment using common lines (reference free)
| Automatic identification of filaments in micrographs
|-  
|-  


| Paper
| Paper
| [[1988Provencher_Simultaneous]]
| [[2004Sigworth_Detection]]
| Simultaneaous alignment and reconstruction
| Classical detection theory and the cryo-EM particle selection problem
|-  
|-  


| Paper
| Paper
| [[1988Radermacher_RCT]]
| [[2004Volkmann_ParticlePicking]]
| Random Conical Tilt and Single axis tilt
| An approach to automated particle picking from electron micrographs based on reduced representation templates
|-  
|-  


| Paper
| Paper
| [[1988Vogel_Simultaneous]]
| [[2004Wong_ParticlePicking]]
| Simultaneaous alignment and reconstruction
| Model-based particle picking for cryo-electron microscopy
|-  
|-  


| Paper
| Paper
| [[1990Gelfand_Moments]]
| [[2004Zhu_Review]]
| Angular assignment using moments (reference free)
| Review on automatic particle picking
|-  
|-  


| Paper
| Paper
| [[1990Goncharov_Moments]]
| [[2007Chen_Signature]]
| Angular assignment using moments (reference free)
| Automatic particle picking program: Signature
|-  
|-  


| Paper
| Paper
| [[1990Harauz_Quaternions]]
| [[2007Woolford_SwarmPS]]
| Use of quaternions to represent rotations
| Automatic particle picking with several criteria, implemented in EMAN Boxer
|-  
|-  


| Paper
| Paper
| [[1994Penczek_Real]]
| [[2009Sorzano_MachineLearning]]
| Angular assignment using projection matching in real space
| Automatic particle picking based on machine learning of rotational invariants
|-  
|-  


| Paper
| Paper
| [[1994Radermacher_Radon]]
| [[2011Arbelaez_Comparison]]
| Angular assignment in Radon space
| Evaluation of the performance of software for automated particle-boxing
|-  
|-


| Paper
| Paper
| [[1996Penczek_CommonLines]]
| [[2013Abrishami_MachineLearning]]
| Angular assignment using common lines (reference free)
| 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
| Paper
| [[2003Rosenthal_DPR]]
| [[2013Vargas_ParticleQuality]]
| Angular assignment using DPR
| Automatic determination of particle quality
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Wavelet]]
| [[2014Langlois_ParticlePicking]]
| Angular assignment in the wavelet space.
| Automatic particle picking
|-  
|-  


| Paper
| Paper
| [[2005Jonic_Splines]]
| [[2015Scheres_SemiAutoPicking]]
| Angular assignment in Fourier space using spline interpolation.
| Semi-automated selection of cryo-EM particles
|-  
|-  


| Paper
| Paper
| [[2005Yang_Simultaneous]]
| [[2016Vilas_AutomaticTilt]]
| Simultaneaous alignment and reconstruction
| Automatic identification of image pairs in untilted-tilted micrograph pairs
|-  
|-  


| Paper
| Paper
| [[2006Ogura_SimulatedAnnealing]]
| [[2016Wang_DeepPicker]]
| Angular asignment by simulated annealing
| A deep learning approach for fully automated particle picking
|-  
|-  


| Paper
| Paper
| [[2007Grigorieff_Continuous]]
| [[2017Rickgauer_Detection]]
| Continuous angular assignment in Fourier space
| Picking by correlation
|-  
|-  


| Paper
| Paper
| [[2010Jaitly_Bayesian]]
| [[2017Zhu_DeepEM]]
| Angular assignment by a Bayesian method and annealing
| Deep learning approach to picking
|-
|-  


| Paper
| Paper
| [[2010Sanz_Random]]
| [[2018Huber_Helices]]
| Random model method
| Automated tracing of helices
|-
|-  


| Paper
| Paper
| [[2010Singer_Voting]]
| [[2018Heimowitz_ApplePicker]]
| Detecting consistent common lines by voting (reference free)
| Automated particle picking
|-
|-  


| Paper
| Paper
| [[2011Singer_SDP]]
| [[2018Sanchez_DeepConsensus]]
| Angular assignment by semidefinite programming and eigenvectors (reference free)
| Deep learning consensus of multiple automatic pickers
|-
|-  


| Paper
| Paper
| [[2012Giannakis_Scattering]]
| [[2019Alazzawi_Clustering]]
| Construction of an initial volume, reference free, by graph analysis of the projections
| Use of clustering algorithms to find particles in micrographs
|-
|-  


| Paper
| Paper
| [[2012Shkolnisky_Sync]]
| [[2019Bepler_Topaz]]
| Angular assignment by synchronization of rotations (reference free)
| Deep learning for particle picking
|-
|-  


| Paper
| Paper
| [[2013Elmlund H_PRIME]]
| [[2019Carrasco_IP]]
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
| Use of standard image processing for particle picking
|-  
 
| Conference
| [[2019Li_Deep]]
| Deep learning for particle picking without box size
|-  
|-  


| Paper
| Paper
| [[2013Wang_LUD]]
| [[2019Wagner_Cryolo]]
| Angular assignment by least unsquared deviations (reference free)
| Deep learning for particle picking
|-
|-  


| Paper
| Paper
| [[2014Vargas_RANSAC]]
| [[2019Wang_Biobjective]]
| Initial model using RANSAC (reference free)
| Biobjective function for robust signal detection
|-
|-  


| Paper
| Paper
| [[2015Joubert_Pseudoatoms]]
| [[2019Zhang_Pixer]]
| Initial model based on pseudo-atoms
| Deep learning for particle picking
|-  
|-  


| Paper
| Paper
| [[2015Singer_Kam]]
| [[2020Sanchez_Cleaner]]
| Reconstruction without angular assignment from autocorrelation function (reference free)
| Deep learning for removing particles from the carbon edges, aggregations, contaminations, ...
|-
 
| Conference
| [[2021Li_PickerOptimizers]]
| Removal of badly picked particles with Deep Learning
|-  
|-  


| Paper
| Paper
| [[2015Sorzano_Significant]]
| [[2021Ohashi_GRIPS]]
| Statistical approach to the initial volume estimation (reconstruct significant)
| Two-pass picking with GRIPS
|-  
|-  


| Paper
| Paper
| [[2016Cossio_BayesianGPU]]
| [[2022Eldar_ASOCEM]]
| GPU implementation of the Bayesian 3D reconstruction approach
| Automatic segmentation of contaminations
|-  
|-  


| Conference
| Conference
| [[2016Michels_Heterogeneous]]
| [[2022Huang_DenoisingAndPicking]]
| Initial volume in the presence of heterogeneity
| Simultaneous denoising and picking with deep learning
|-  
|-  


| Paper
| Paper
| [[2016Pragier_Graph]]
| [[2022Kreymer_MTD]]
| Graph partitioning approach to angular reconstitution
| Expectation-Maximization approach to particle picking
|-  
|-  


| Paper
| Paper
| [[2017Greenberg_CommonLines]]
| [[2022Olek_Icebreaker]]
| Common lines for reference free ab-initio reconstruction
| Ice thickness detection and its use for particle picking
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Highres]]
| [[2022Zhang_EPicker]]
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
| Particle picking based on continual learning
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Swarm]]
| [[2023Dhakal_CryoPPP]]
| Consensus of several initial volumes by swarm optimization
| A public database for particle picking
|-  
|-  


| Paper
| Paper
| [[2019Zehni_Joint]]
| [[2023Lucas_Baited]]
| Continuous angular refinement and reconstruction
| Baited reconstruction with 2D template matching
|-  
|-  


| Paper
| Paper
| [[2020Xie_Network]]
| [[2024Anuk_Auction]]
| Angular assignment considering a network of assignments
| Particle picking using combinatorial auction
|-  
|-  


| Paper
| Paper
| [[2020Zehni_Joint]]
| [[2024Cameron_REPIC]]
| Continuous angular refinement and reconstruction
| Consensus 2D particle picking using graphs
|-  
|-  


| Paper
| Paper
| [[2020Singer_NonUniformKam]]
| [[2024Fang_Swin]]
| Reconstruction and angular distribution estimation without angular assignment (reference free)
| SwinCryoEM: particle picking
|-  
|-  


|}
| Paper
| [[2024Gyawali_CryoSegNet]]
| CryoSegNet: particle picking
|-


=== 3D Reconstruction ===
| Paper
{|
| [[2024Huang_Joint]]
| Joint denoising and picking
|-


| Paper
| Paper
| [[1972Gilbert_SIRT]]
| [[2025Chung_CRISP]]
| Simultaneous Iterative Reconstruction Technique (SIRT)
| Particle picking with deep learning and Conditional Random Field layers
|-  
|-  


| Paper
| Paper
| [[1973Herman_ART]]
| [[2025Dhakal_Benchmark]]
| Algebraic Reconstruction Technique (ART)
| Benchmark of particle picking with deep learning
|-  
|-  


| Paper
| Paper
| [[1980Kam_SphericalHarmonics]]
| [[2025Neiterman_Frames]]
| 3D Reconstruction using spherical harmonics
| Particle picking at the level of frames
|-  
|-  


| Paper
| Paper
| [[1984Andersen_SART]]
| [[2025Ni_GTPick]]
| Simultaneous Algebraic Reconstruction Technique (SART)
| GTPick: Particle picking with deep learning
|-  
|-  


| Paper
| Paper
| [[1986Harauz_FBP]]
| [[2025Zamanos_CryoEMMAE]]
| Exact filters for Filtered Back Projection
| Fully unsupervised particle picking using neural networks
|-  
|-  


| Chapter
| Paper
| [[1992Radermacher_WBP]]
| [[2025Zhang_2DTMpValue]]
| Exact filters for Weighted Back Projection
| p-value of the 2D template matching SNR and z-scores
|-  
|-  
|}
=== 2D Preprocessing ===
{|


| Paper
| Paper
| [[1997Zhu_RecCTF]]
| [[1978Carrascosa_matching]]
| 3D Reconstruction (SIRT like) and simultaneous CTF correction
| Gray values matching by linear transformations
|-  
|-  


| Paper
| Paper
| [[1998Boisset_Uneven]]
| [[2003Rosenthal_DPR]]
| Artifacts in SIRT and WBP under uneven angular distributions
| Contrast enhancement through DPR
|-  
|-  


| Paper
| Paper
| [[1998Marabini_ART]]
| [[2004Sorzano_Normalization]]
| Algebraic Reconstruction Technique with blobs (Xmipp)
| Normalization procedures and their statistical properties.
|-  
|-  


| Paper
| Paper
| [[2001Sorzano_Uneven]]
| [[2006Sorzano_Denoising]]
| Free parameter selection under uneven angular distributions
| Strong denoising in wavelet space
|-  
|-  


| Paper
| Conference
| [[2005Sorzano_Parameters]]
| [[2009Sorzano_Downsampling]]
| Free parameter selection for optimizing multiple tasks
| Differences between the different downsampling schemes
|-  
|-  


| Paper
| Paper
| [[2008Sorzano_Constraints]]
| [[2012Brilot_Movies]]
| Mass, surface, positivity and symmetry constraints for real-space algorithms
| Alignment of beam induced motion in direct detectors
|-  
|-  


| Paper
| Paper
| [[2009Bilbao_ParallelART]]
| [[2012Campbell_Movies]]
| Efficient parallelization of ART
| Alignment of beam induced motion in direct detectors
|-  
|-  


| Paper
| Paper
| [[2011Li_GradientFlow]]
| [[2012Zhao_Denoising]]
| Regularized 3D Reconstruction by Gradient Flow
| Denoising using an invariant Fourier-Bessel eigenspace
|-  
|-  


| Paper
| Paper
| [[2011Vonesch_Wavelets]]
| [[2013Norousi_Screening]]
| Fast wavelet-based 3D reconstruction
| Screening particles to identify outliers
|-  
|-  


| Paper
| Paper
| [[2012Gopinath_ShapeRegularization]]
| [[2013Bai_ElectronCounting]]
| Regularized 3D Reconstruction by Shape information
| Electron counting and beam induced motion correction
|-  
|-  


| Paper
| Paper
| [[2012Kucukelbir_adaptiveBasis]]
| [[2013Li_ElectronCounting]]
| 3D reconstruction in an adaptive basis promoting sparsity
| Electron counting and beam induced motion correction
|-  
|-  


| Paper
| Paper
| [[2012Sindelar_NoiseReduction]]
| [[2013Shigematsu_Movies]]
| Optimal noise reduction in 3D reconstructions
| Drift correction for movies considering dark field
|-  
|-  


| Paper
| Paper
| [[2013Elmlund H_PRIME]]
| [[2013Vargas_ParticleQuality]]
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
| Automatic determination of particle quality
|-  
|-  


| Paper
| Paper
| [[2013Lyumkis_Optimod]]
| [[2014Scheres_Movies]]
| Construction of initial volumes with Optimod
| Beam induced motion correction
|-  
|-  


| Paper
| Paper
| [[2013Wang FIRM]]
| [[2015Abrishami_Movies]]
| Fast 3D reconstruction in Fourier domain
| Alignment of direct detection device micrographs
|-  
|-  


| Paper
| Paper
| [[2014Kunz_SART_OS]]
| [[2015Grant_Anisotropic]]
| Simultaneous ART with OS
| Automatic estimation and correction of anisotropic magnification
|-  
|-  


| Paper
| Paper
| [[2015Abrishami_Fourier]]
| [[2015Grant_OptimalExposure]]
| 3D Reconstruction in Fourier space
| Filter movies according to the radiation damage
|-  
|-  


| Paper
| Paper
| [[2015Dvornek_SubspaceEM]]
| [[2015Rubinstein_Alignment]]
| Fast Maximum a posteriori
| Frame alignment at the level of particle
|-
 
| Conference
| [[2018Michels_RBF]]
| Ab-initio reconstruction with radial basis functions
|-  
|-  


| Paper
| Paper
| [[2015Moriya_Bayesian]]
| [[2015Spear_DoseCompensation]]
| Bayesian approach to suppress limited angular artifacts
| Effect of dose compensation on resolution
|-  
|-  


| Paper
| Paper
| [[2015Xu_GeometricFlow]]
| [[2015Zhao_AnisotropicMagnification]]
| Multi-scale geometric flow
| Correction of anisotropic magnification
|-  
|-  


| Arxiv
| Conference
| [[2016Ye_Cohomology]]
| [[2016Bajic_Denoising]]
| Cohomology properties of 3D reconstruction
| Denoising and deconvolution of micrographs
|-  
|-  


| Paper
| Paper
| [[2017Punjani_CryoSPARC]]
| [[2016Jensen_RemovalVesicles]]
| CryoSPARC
| Removal of vesicles in membrane proteins
|-  
|-  


| Paper
| Paper
| [[2017Punjani_CryoSPARCTheory]]
| [[2016Bhamre_Denoising]]
| Theory related to CryoSPARC
| Denoising by 2D covariance estimation
|-  
|-  


| Paper
| Paper
| [[2017Sorzano_SurveyIterative]]
| [[2017Berndsen_EMPH]]
| Survey of iterative reconstruction methods for EM
| Automated hole masking algorithm
|-  
|-  


| Paper
| Paper
| [[2018Bartesaghi_Refinement]]
| [[2017McLeod_Zorro]]
| Refinement of CTF, frame weight and alignment for high resolution reconstruction
| Movie alignment by Zorro
|-  
|-  


| Paper
| Paper
| [[2018Hu_ParticleFilter]]
| [[2017Zheng_MotionCorr2]]
| A particle filter framework for 3D reconstruction
| Movie alignment by MotionCorr2
|-  
|-  


| Conference
| Paper
| [[2018Levin_Kam]]
| [[2018Ouyang_Denoising]]
| Ab initio reconstruction by autocorrelation analysis
| Denoising based on geodesic distance
|-  
|-  


| Paper
| Paper
| [[2018Reboul_Simple]]
| [[2018Wu_ContrastEnhancement]]
| Ab initio reconstruction with Simple
| Contrast enhancement
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Highres]]
| [[2019Zivanov_BayesianBIM]]
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
| Bayesian correction of beam induced movement
|-  
|-  


| Paper
| Paper
| [[2018Sorzano_Swarm]]
| [[2020Bepler_TopazDenoise]]
| Consensus of several initial volumes by swarm optimization
| Preprocessing of micrographs for better picking
|-  
|-  


| Paper
| Paper
| [[2018Zhu_Ewald]]
| [[2020Chung_2SDR]]
| 3D Reconstruction with Ewald sphere correction
| PCA to denoise particles
|-  
|-  


| Paper
| Paper
| [[2019Gomez_Initial]]
| [[2020Chung_Prepro]]
| Construction of initial models
| Preprocessing of particles for better alignment
|-  
|-  


| Master
| Conference
| [[2019Havelkova_Regularization]]
| [[2020Huang_SuperResolution]]
| Regularization methods in 3D reconstruction
| Deep learning superresolution combination of frames
|-  
|-  


| Paper
| Paper
| [[2019Wilkinson_Scales]]
| [[2020Palovcak_noise2noise]]
| Combining data acquired at different scales
| Noise2noise denoising of micrographs
|-  
|-  


| Paper
| Paper
| [[2020Alazzawi_Auto]]
| [[2020Strelak_FlexAlign]]
| Automatic full processing of micrographs to yield a 3D reconstruction
| Continuous deformation model for aligning movie frames
|-
 
| Conference
| [[2021Fan_Denoising]]
| Particle denoising using vector diffusion maps
|-  
|-  


| Paper
| Paper
| [[2020Pan_TV]]
| [[2022Heymann_ProgressiveSSNR]]
| 3D Reconstruction with total variation regularization
| Progressive SSNR to assess quality and radiation damage
|-  
|-  


| Paper
| Paper
| [[2020Punjani_NonUniform]]
| [[2022Shi_Denoising]]
| Non-uniform refinement
| Contrast estimation and denoising in SPA
|-  
|-  


| Paper
| Paper
| [[2020Ramlaul_Sidesplitter]]
| [[2023Huang_ZSSR]]
| Local filtering along the reconstruction iterations
| Multiple image super-resolution, upsampling with deep learning
|-  
|-  


| Paper
| Paper
| [[2020Xie_Automatic]]
| [[2023Marshall_PCA]]
| Automatic 3D reconstruction from projections
| Fast PCA on single particle images
|-  
|-  


| Paper
| Paper
| [[2020Zhou_AutomaticSelection]]
| [[2023Sharon_Enhancement]]
| Automatic selection of particles for 3D reconstruction
| Signal enhancement of SPA particles
|-  
|-  


| Paper
| Paper
| [[2021Luo_Opus]]
| [[2023Strelak_MovieAlignment]]
| 3D Reconstruction with a sparse and smoothness constraint
| Comparison of movie alignment programs
|-  
|-  


| Paper
| Paper
| [[2021Kimanius_PriorKnowledge]]
| [[2023Zhang_Denoising]]
| Incorporation of prior knowledge during 3D reconstruction
| Single Particle denoising using Deep Convolutional autoencoder and K-means++
|-  
|-  


| Paper
| Paper
| [[2021Sorzano_Uneven]]
| [[2024Li_Subtraction]]
| Algorithmic robustness to uneven angular distributions
| Subtraction of membrane signal in SPA
|-  
|-  


|}
|}


=== 3D Heterogeneity ===
=== 2D Alignment ===


{|
{|


| Paper
| Paper
| [[2004White_Size]]
| [[1981Frank_Averaging]]
| Heterogeneity classification of differently sized images
| 2D averaging and phase residual
|-  
|-  


| Paper
| Paper
| [[2006Penczek_Bootstrap]]
| [[1982Saxton_Averaging]]
| 3D heterogeneity through bootstrap
| 2D averaging using correlation
|-  
|-  


| Paper
| Paper
| [[2007Leschziner_Review]]
| [[1998Sigworth_ML2D]]
| Review of 3D heterogeneity handling algorithms
| Maximum likelihood alignment in 2D
|-  
|-  


| Paper
| Paper
| [[2007Scheres_ML3D]]
| [[2003Cong_FRM2D]]
| Maximum Likelihood alignment and classification in 3D
| Fast Rotational Matching in 2D
|-  
|-  


| Paper
| Paper
| [[2008Herman_Graph]]
| [[2005Cong_FRM2D]]
| Classification by graph partitioning
| Fast Rotational Matching in 2D introduced in a 3D Alignment algorithm
|-  
|-  


| Paper
| Paper
| [[2009Spahn_Bootstrap]]
| [[2005Scheres_ML2D]]
| 3D heterogeneity through bootstrap
| Multireference alignment and classification in 2D
|-  
|-  


| Paper
| Paper
| [[2010Elmlund_AbInitio]]
| [[2016Aguerrebere_Limits]]
| Solving the initial volume problem with multiple conformations
| Fundamental limits of 2D translational alignment
|-  
|-  


| Paper
| Paper
| [[2010Shatsky_MultiVariate]]
| [[2010Sorzano_CL2D]]
| Multivariate Statistical Analysis
| Multireference alignment and classification in 2D
|-
 
| Conference
| [[2017Anoshina_Correlation]]
| New correlation measure for aligning images
|-  
|-  


| Paper
| Paper
| [[2012Scheres_Bayesian]]
| [[2019Radermacher_Correlation]]
| A Bayesian view on cryo-EM structure determination
| On the properties of cross correlation for the alignment of images
|-  
|-  


| Paper
| Paper
| [[2012Zheng_Covariance]]
| [[2020Lederman_representation]]
| Estimation of the volume covariance
| A representation theory perspective of alignment and classification
|-  
|-  


| Paper
| Paper
| [[2013Wang_MLVariance]]
| [[2020Marshall_Invariants]]
| Maximum Likelihood estimate of the map variance
| Recovery of an image from its invariants
|-  
|-  


| Paper
| Paper
| [[2013Lyumkis D_FREALIGN]]
| [[2021Chen_Fast]]
| Likelihood-based classification of cryo-EM images using FREALIGN.
| Fast alignment through Power Spectrum
|-
|-  


| Paper
| Conference
| [[2014Jin_NMA]]
| [[2021Chung_CryoRALIB]]
| Continuous heterogeneity through Normal Mode Analysis
| Image alignment acceleration
|-  
|-  


| Paper
| Paper
| [[2014Dashti_Brownian]]
| [[2021Heimowitz_Centering]]
| Continuous heterogeneity through Brownian trajectories
| Centering noisy images
|-  
|-  


| Paper
| Conference
| [[2014Chen_Migration]]
| [[2022Bendory_Complexity]]
| Particle migration analysis in 3D classification
| Computational complexity of multireference image alignment
|-  
|-  


| Paper
| Paper
| [[2015Anden_Covariance]]
| [[2024Bendory_Complexity]]
| 3D Covariance matrix estimation for heterogeneity
| Computational complexity of multireference image alignment
|-  
|-  


| Paper
| Paper
| [[2015Bai_Focused]]
| [[2024Bai_NUFT]]
| Focused classification  
| 2D Image classification based on the Non-uniform Fourier Transform
|-  
|-  


| Paper
| Paper
| [[2015Katsevich_Covariance]]
| [[2025Kapnulin_Outlier]]
| 3D Covariance matrix estimation for heterogeneity
| 2D Outlier rejection based on radial averages
|-  
|-  
|}
=== 2D Classification and clustering ===
{|


| Paper
| Paper
| [[2015Klaholz_MRA]]
| [[1981VanHeel_MSA]]
| Multivariate Statistical Analysis of Jackknife and Bootstrapping on random subsets
| Multivariate Statistical Analysis
|-  
|-  


| Paper
| Paper
| [[2015Liao_Covariance]]
| [[1984VanHeel_MSA]]
| Estimation of the 3D covariance from 2D projections
| Multivariate Statistical Analysis
|-  
|-  


| Paper
| Paper
| [[2015Tagare_Direct]]
| [[2005Scheres_ML2D]]
| Direct reconstruction of PCA components
| Multireference alignment and classification in 2D
|-  
|-  


| Paper
| Paper
| [[2016Gong_Mechanical]]
| [[2010Sorzano_CL2D]]
| Mechanical model for macromolecules
| Multireference alignment and classification in 2D
|-  
|-  


| Paper
| Paper
| [[2016Rawson_Movement]]
| [[2011Singer_DiffusionMaps]]
| Movement and flexibility
| Classification in 2D based on graph analysis of the projections
|-  
|-  


| Paper
| Paper
| [[2016Shan_Multibody]]
| [[2012Yang_ISAC]]
| Multibody refinement
| Iterative Stable Alignment and clustering
|-  
|-  


| Paper
| Paper
| [[2016Sorzano_StructMap]]
| [[2014Sorzano_Outlier]]
| Sorting a discrete set of conformational states
| Outlier detection in 2D classifications.
|-  
|-  


| Paper
| Paper
| [[2016Sorzano_Strain]]
| [[2014Zhao_Aspire]]
| Calculate local stretches, strains and rotations from two conformational states
| Fast classification based on rotational invariants and vector diffusion maps
|-  
|-  


| Paper
| Paper
| [[2017Punjani_CryoSPARC]]
| [[2015Huang_Robust]]
| CryoSPARC
| Robust w-estimators of 2D classes
|-  
|-  


| Paper
| Paper
| [[2017Schillbach_Warpcraft]]
| [[2016Kimanius_Accelerated]]
| Warpcraft: 3D Reconstruction in the presence of continuous heterogeneity
| GPU Accelerated image classification and high-resolution refinement
|-  
|-  


| Paper
| Paper
| [[2018Anden_Covariance]]
| [[2016Reboul_Stochastic]]
| Structural Variability from Noisy Tomographic Projections
| Stochastic Hill Climbing for calculating 2D classes
|-
 
| Conference
| [[2017Bhamre_Mahalanobis]]
| 2D classification using Mahalanobis distance
|-  
|-  


| Paper
| Paper
| [[2018Haselbach_FreeEnergy]]
| [[2017Wu_GTM]]
| Analysis of the free energy landscape through PCA
| 2D classification using Generative Topographic Mapping
|-
 
| Conference
| [[2018Boumal_SinglePass]]
| Single pass classification
|-  
|-  


| Paper
| Conference
| [[2018Nakane_MultiBody]]
| [[2018Shuo_Network]]
| Structural Variability through multi-body refinement
| 2D Clustering by network metrics
|-  
|-  


| Paper
| Paper
| [[2019Serna_Review]]
| [[2020Ma_RotationInvariant]]
| Review of classification tools
| 2D heterogeneity determination by rotation invariant features
|-  
|-  


| Paper
| Conference
| [[2018Solernou_FFEA]]
| [[2020Miolane_VAEGAN]]
| Fluctuating Finite Element Analysis, continuum approach to Molecular Dynamics
| 2D Analysis by deep learning
|-  
|-  


| Paper
| Conference
| [[2019Sorzano_Review]]
| [[2021Rao_Wasserstein]]
| Review of continuous heterogeneity biophysics
| Wasserstein K-Means for Clustering Tomographic Projections
|-  
|-  


| Paper
| Paper
| [[2019Zhang_Local]]
| [[2022Vilela_Feret]]
| Local variability and covariance
| 2D heterogeneity detection through Feret signatures
|-  
|-  


| Paper
| Paper
| [[2020Harastani_NMA]]
| [[2022Wang_Spectral]]
| Using Scipion for analyzing local heterogeneity with normal modes
| 2D classification with spectral clustering
|-  
|-  


| Paper
| Paper
| [[2020Maji_Propagation]]
| [[2022Zhang_DRVAE]]
| Propagation of conformational coordinates across angular space
| 2D classification with deep learning and K-means++
|-  
|-  


| Paper
| Paper
| [[2020Zhong_CryoDRGN]]
| [[2023Chen_Joint]]
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
| 2D classification with deep learning and joint unsupervised difference learning
|-  
|-  


| Paper
| Conference
| [[2020Moscovich_DiffusionMaps]]
| [[2023Weiss_Noise]]
| Heterogeneity analysis by diffusion maps and spectral volumes
| Identifying non-particles with probabilistic PCA
|-  
|-  


| Paper
| Paper
| [[2021Matsumoto_DEFmap]]
| [[2024Tang_SimCryoCluster]]
| Prediction of RMSF of Molecular Dynamics from a CryoEM map using deep learning
| SimCryoCluster: 2D classification in SPA using a deep clustering method
|-  
|-  


| Paper
| Paper
| [[2021Zhong_CryoDRGN]]
| [[2025Bai_NUDFT]]
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
| 2D Classification in SPA using the Non-uniform DFT
|-  
|-  


|}
|}


=== Validation ===
=== 3D Alignment ===


{|
{|


| Paper
| Paper
| [[2008Stagg_TestBed]]
| [[1980Kam_AutoCorrelation]]
| Effect of voltage, dosis, number of particles and Euler jumps on resolution
| Reconstruction without angular assignment from autocorrelation function (reference free)
|-  
|-  


| Paper
| Paper
| [[2011Henderson]]
| [[1986Goncharov_CommonLines]]
| Tilt Validation
| Angular assignment using common lines (reference free)
|-  
|-  


| Paper
| Paper
| [[2011Read]]
| [[1987VanHeel_CommonLines]]
| Validation of PDBs
| Angular assignment using common lines (reference free)
|-  
|-  


| Paper
| Paper
| [[2012Henderson]]
| [[1988Provencher_Simultaneous]]
| EM Map Validation
| Simultaneaous alignment and reconstruction
|-  
|-  


| Paper
| Paper
| [[2013Cossio_Bayesian]]
| [[1988Radermacher_RCT]]
| EM Map Validation in a probabilistic setting
| Random Conical Tilt and Single axis tilt
|-  
|-  


| Paper
| Paper
| [[2013Chen_NoiseSubstitution]]
| [[1988Vogel_Simultaneous]]
| Noise substitution at high resolution for measuring overfitting
| Simultaneaous alignment and reconstruction
|-  
|-  


| Paper
| Paper
| [[2013Ludtke_Validation]]
| [[1990Gelfand_Moments]]
| Structural validation, example of the Calcium release channel
| Angular assignment using moments (reference free)
|-  
|-  


| Paper
| Paper
| [[2013Murray_Validation]]
| [[1990Goncharov_Moments]]
| Validation of a 3DEM structure through a particular example
| Angular assignment using moments (reference free)
|-  
|-  


| Paper
| Paper
| [[2014Russo_StatisticalSignificance]]
| [[1990Harauz_Quaternions]]
| EM Map Validation through the statistical significance of the tilt-pair angular assignment
| Use of quaternions to represent rotations
|-  
|-  


| Paper
| Paper
| [[2014Stagg_Reslog]]
| [[1994Penczek_Real]]
| EM Map Validation through the resolution evolution with the number of particles
| Angular assignment using projection matching in real space
|-  
|-  


| Paper
| Paper
| [[2014Wasilewski_Tilt]]
| [[1994Radermacher_Radon]]
| Web implementation of the tilt pair validation
| Angular assignment in Radon space
|-  
|-  


| Paper
| Paper
| [[2015Heymann_Alignability]]
| [[1996Penczek_CommonLines]]
| EM Map Validation through the resolution of reconstructions from particles and noise
| Angular assignment using common lines (reference free)
|-  
|-  


| Paper
| Paper
| [[2015Oliveira_FreqLimited]]
| [[2003Rosenthal_DPR]]
| Comparison of gold standard and frequency limited optimization
| Angular assignment using DPR
|-  
|-  


| Paper
| Paper
| [[2015Rosenthal_Review]]
| [[2004Sorzano_Wavelet]]
| Review of validation methods
| Angular assignment in the wavelet space.
|-  
|-  


| Paper
| Paper
| [[2015Wriggers_Secondary]]
| [[2005Jonic_Splines]]
| Validation by secondary structure
| Angular assignment in Fourier space using spline interpolation.
|-  
|-  


| Paper
| Paper
| [[2016Degiacomi_IM]]
| [[2005Yang_Simultaneous]]
| Comparison of Ion Mobility data and EM volumes
| Simultaneaous alignment and reconstruction
|-  
|-  


| Paper
| Paper
| [[2016Kim_SAXS]]
| [[2006Ogura_SimulatedAnnealing]]
| Comparison of SAXS data and EM projections
| Angular asignment by simulated annealing
|-  
|-  


| Paper
| Paper
| [[2016Rosenthal_Review]]
| [[2007Grigorieff_Continuous]]
| Review of validation methods
| Continuous angular assignment in Fourier space
|-  
|-  


| Paper
| Paper
| [[2016Vargas_Alignability]]
| [[2010Jaitly_Bayesian]]
| Validation by studying the tendency of an angular assignment to cluster in the projection space
| Angular assignment by a Bayesian method and annealing
|-  
|-


| Paper
| Paper
| [[2017Monroe_PDBRefinement]]
| [[2010Sanz_Random]]
| Validation by comparison to a refined PDB
| Random model method
|-  
|-


| Paper
| Paper
| [[2018Afonine_Phenix]]
| [[2010Singer_Voting]]
| Tools in Phenix for the validation of EM maps
| Detecting consistent common lines by voting (reference free)
|-  
|-


| Paper
| Paper
| [[2018Heymann_Bsoft]]
| [[2011Singer_SDP]]
| Map validation using Bsoft
| Angular assignment by semidefinite programming and eigenvectors (reference free)
|-  
|-


| Paper
| Paper
| [[2018Heymann_Challenge]]
| [[2012Giannakis_Scattering]]
| A summary of the assessments of the 3D Map Challenge
| Construction of an initial volume, reference free, by graph analysis of the projections
|-  
|-


| Paper
| Paper
| [[2018Jonic_Gaussian]]
| [[2012Shkolnisky_Sync]]
| Assessment of sets of volumes by pseudoatomic structures
| Angular assignment by synchronization of rotations (reference free)
|-  
|-


| Paper
| Paper
| [[2018Naydenova_AngularDistribution]]
| [[2013Elmlund H_PRIME]]
| Evaluating the angular distribution of a 3D reconstruction
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
|-  
|-  


| Paper
| Paper
| [[2018Pages_Symmetry]]
| [[2013Wang_LUD]]
| Looking for a symmetry axis in a PDB
| Angular assignment by least unsquared deviations (reference free)
|-  
|-


| Paper
| Paper
| [[2018Pintilie_SSE]]
| [[2014Vargas_RANSAC]]
| Evaluating the quality of SSE and side chains
| Initial model using RANSAC (reference free)
|-  
|-


| Paper
| Paper
| [[2019Herzik_Multimodel]]
| [[2015Joubert_Pseudoatoms]]
| Local and global quality by multi-model fitting
| Initial model based on pseudo-atoms
|-  
|-  


| Paper
| Paper
| [[2020Chen_Atomic]]
| [[2015Singer_Kam]]
| Validation of the atomic models derived from CryoEM
| Reconstruction without angular assignment from autocorrelation function (reference free)
|-  
|-  


| Paper
| Paper
| [[2020Cossio_CrossValidation]]
| [[2015Sorzano_Significant]]
| Need for cross validation
| Statistical approach to the initial volume estimation (reconstruct significant)
|-  
|-  


| Paper
| Paper
| [[2020Ortiz_CrossValidation]]
| [[2016Cossio_BayesianGPU]]
| Cross validation for SPA
| GPU implementation of the Bayesian 3D reconstruction approach
|-  
|-  


| Paper
| Conference
| [[2020Sazzed_helices]]
| [[2016Michels_Heterogeneous]]
| Validation of helix quality
| Initial volume in the presence of heterogeneity
|-  
|-  


| Paper
| Paper
| [[2020Stojkovic_PTM]]
| [[2016Pragier_Graph]]
| Validation of post-translational modifications
| Graph partitioning approach to angular reconstitution
|-  
|-  


| Paper
| Paper
| [[2020Tiwari_PixelSize]]
| [[2017Greenberg_CommonLines]]
| Fine determination of the pixel size
| Common lines for reference free ab-initio reconstruction
|-  
|-  
|}
=== Resolution ===
{|


| Paper
| Paper
| [[1986Harauz_FBP]]
| [[2018Sorzano_Highres]]
| Fourier Shell Correlation
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
|-  
|-  


| Paper
| Paper
| [[1987Unser_SSNR]]
| [[2018Sorzano_Swarm]]
| 2D Spectral Signal to Noise Ratio
| Consensus of several initial volumes by swarm optimization
|-  
|-  


| Paper
| Paper
| [[2002Penczek_SSNR]]
| [[2019Zehni_Joint]]
| 3D Spectral Signal to Noise Ratio for Fourier based algorithms
| Continuous angular refinement and reconstruction
|-  
|-  


| Paper
| Paper
| [[2003Rosenthal_DPR]]
| [[2019Zehni_Joint]]
| Review of the FSC and establishment of a new threshold
| Continuous angular refinement and reconstruction
|-  
|-  


| Paper
| Paper
| [[2005Unser_SSNR]]
| [[2020Sharon_NonUniformKam]]
| 3D Spectral Signal to Noise Ratio for any kind of algorithms
| Reconstruction and angular distribution estimation without angular assignment (reference free)
|-  
|-  


| Paper
| Paper
| [[2005VanHeel_FSC]]
| [[2020Xie_Network]]
| Establishment of a new threshold for FSC
| Angular assignment considering a network of assignments
|-  
|-  


| Paper
| Paper
| [[2007Sousa_AbInitio]]
| [[2021Jimenez_DeepAlign]]
| Resolution measurement on neighbour Fourier voxels
| Angular alignment using deep learning
|-  
|-  


| Paper
| Paper
| [[2014Kucukelbir_Local]]
| [[2021Kojima_Preferred]]
| Quantifying the local resolution of cryo-EM density maps
| Identification of preferred orientations
|-  
|-  


| Paper
| Conference
| [[2016Pintilie_Probabilistic]]
| [[2021Nashed_CryoPoseNet]]
| Probabilistic models and resolution
| CryoPoseNet: Angular alignment with deep learning
|-  
|-  


| Paper
| Conference
| [[2017Sorzano_FourierProperties]]
| [[2021Zhong_CryoDRGN2]]
| Statistical properties of resolution measures defined in Fourier space
| CryoDRGN2: Angular alignment with deep learning
|-  
|-  


| Conference
| Conference
| [[2018Avramov_DeepLearning]]
| [[2022Levy_CryoAI]]
| Deep learning classification of volumes into low, medium and high resolution
| CryoAI: Angular assignment through neural network
|-  
|-  


| Paper
| Paper
| [[2018Carugo_BFactors]]
| [[2022Lian_Neural]]
| How large can B-factors be in protein crystals
| Angular assignment through neural network
|-  
|-  


| Paper
| Paper
| [[2018Kim_FourierError]]
| [[2022Lu_SphericalEmbeddings]]
| Comparison between a gold standard and a reconstruction
| Angular assignment through common lines and spherical embeddings
|-  
|-  


| Paper
| Paper
| [[2018Rupp_Problems]]
| [[2022Wang_Thunder]]
| Problems of resolution as a proxy number for map quality
| Angular assignment implementation in GPU
|-  
|-  


| Paper
| Conference
| [[2018Vilas_MonoRes]]
| [[2023Cesa_Alignment]]
| Local resolution by monogenic signals
| 3D alignment based on deep learning and equivariant representations
|-  
|-  


| Paper
| Paper
| [[2018Yang_Multiscale]]
| [[2023Harpaz_Alignment]]
| Resolution from a multiscale spectral analysis
| Fast alignment of two maps using common lines
|-  
|-  


| Paper
| Paper
| [[2019Avramov_DeepLearning]]
| [[2023Ling_Synch]]
| Deep learning classification of volumes into low, medium and high resolution
| Synchronization of projection directions
|-  
|-  


| Paper
| Paper
| [[2019Ramirez_DeepRes]]
| [[2023Rangan_Fast]]
| Resolution determination by deep learning
| Fast angular assignment using Fourier-Bessel
|-  
|-  


| Paper
| Paper
| [[2020Baldwin_Lyumkis_SCF]]
| [[2023Riahi_Transport]]
| Resolution attenuation through non-uniform Fourier sampling
| Alignment of two 3D maps using Wasserstein's distance
|-  
|-  


| Paper
| Paper
| [[2020Beckers_Permutation]]
| [[2024Chung_CryoForum]]
| Permutation tests for the FSC
| CryoForum: Angular assignment with uncertainty estimation using neural networks
|-  
|-  


| Paper
| Paper
| [[2020Penczek_mFSC]]
| [[2024Muller_Common]]
| Modified FSC to avoid mask induced artifacts
| Initial volume in the presence of heterogeneity using common lines
|-  
|-  


| Paper
| Paper
| [[2020Vilas_MonoDir]]
| [[2024Nottelet_Feret]]
| Local and directional resolution
| Feret signature to detect preferred orientations and misclassified images
|-  
|-  


|}
=== Sharpening of high resolution information ===
{|
| Paper
| Paper
| [[2003Rosenthal_DPR]]
| [[2024Sanchez_Cesped]]
| Contrast restoration and map sharpening
| CESPED: A benchmark for supervised particle pose estimation
|-  
|-  


| Paper
| Conference
| [[2008Fernandez_Bfactor]]
| [[2024Shekarforoush_CryoSPIN]]
| Bfactor determination and restoration
| CryoSpin: Semi-amortized image alignment using deep learning
|-  
|-  


| Paper
| Paper
| [[2013Fiddy_SaxtonAlgorithm]]
| [[2024Singer_Wasserstein]]
| Phase retrieval or extension
| Alignment of two 3D maps using Wasserstein's distance
|-  
|-  


| Paper
| Paper
| [[2014Kishchenko_SphericalDeconvolution]]
| [[2024Titarenko_optimal]]
| Spherical deconvolution
| Optimal 3D angular sampling
|-  
|-  


| Paper
| Paper
| [[2015Spiegel_VISDEM]]
| [[2024Wang_CommonLines]]
| Visualization improvement by the use of pseudoatomic profiles
| 3D Alignment by common lines
|-  
|-  


| Paper
| Paper
| [[2016Jonic_Pseudoatoms]]
| [[2024Zhang_Kam]]
| Approximation with pseudoatoms
| Distance between maps without aligning them
|-  
|-  
|}
=== 3D Reconstruction ===
{|


| Paper
| Paper
| [[2016Jonic_Denoising]]
| [[1972Gilbert_SIRT]]
| Denoising and high-frequency boosting by pseudoatom approximation
| Simultaneous Iterative Reconstruction Technique (SIRT)
|-  
|-  


| Paper
| Paper
| [[2017Jakobi_LocScale]]
| [[1973Herman_ART]]
| Sharpening based on an atomic model
| Algebraic Reconstruction Technique (ART)
|-  
|-  


| Paper
| Paper
| [[2019Ramlaul_Filtering]]
| [[1980Kam_SphericalHarmonics]]
| Local agreement filtering (denoising)
| 3D Reconstruction using spherical harmonics
|-  
|-  


| Paper
| Paper
| [[2020Terwilliger_density]]
| [[1984Andersen_SART]]
| Density modification of CryoEM maps
| Simultaneous Algebraic Reconstruction Technique (SART)
|-  
|-  


| Paper
| Paper
| [[2020Vilas_Bfactor]]
| [[1986Harauz_FBP]]
| Global B-factor correction does not represent macromolecules
| Exact filters for Filtered Back Projection
|-  
|-  


|}
| Chapter
| [[1992Radermacher_WBP]]
| Exact filters for Weighted Back Projection
|-


=== CTF estimation and restoration ===
| Paper
 
| [[1997Zhu_RecCTF]]
{|
| 3D Reconstruction (SIRT like) and simultaneous CTF correction
|-


| Paper
| Paper
| [[1982Schiske_Correction]]
| [[1998Boisset_Uneven]]
| CTF correction for tilted objects
| Artifacts in SIRT and WBP under uneven angular distributions
|-  
|-  


| Paper
| Paper
| [[1988Toyoshima_Model]]
| [[1998Marabini_ART]]
| CTF estimation
| Algebraic Reconstruction Technique with blobs (Xmipp)
|-  
|-  


| Paper
| Paper
| [[1995Frank_Wiener]]
| [[2001Sorzano_Uneven]]
| CTF correction using Wiener filter
| Free parameter selection under uneven angular distributions
|-  
|-  


| Paper
| Paper
| [[1996Skoglund_MaxEnt]]
| [[2005Sorzano_Parameters]]
| CTF correction with Maximum Entropy
| Free parameter selection for optimizing multiple tasks
|-  
|-  


| Paper
| Paper
| [[1996Zhou_Model]]
| [[2008Sorzano_Constraints]]
| CTF model and user interface for manual fitting
| Mass, surface, positivity and symmetry constraints for real-space algorithms
|-  
|-  


| Paper
| Paper
| [[1997Fernandez_AR]]
| [[2009Bilbao_ParallelART]]
| PSD estimation using periodogram averaging and AR models
| Efficient parallelization of ART
|-  
|-  


| Paper
| Paper
| [[1997Penczek_Wiener]]
| [[2011Li_GradientFlow]]
| CTF correction using Wiener filter
| Regularized 3D Reconstruction by Gradient Flow
|-  
|-  


| Paper
| Paper
| [[1997Stark_Deconvolution]]
| [[2011Vonesch_Wavelets]]
| CTF correction using deconvolution
| Fast wavelet-based 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[1997Zhu_RecCTF]]
| [[2012Gopinath_ShapeRegularization]]
| CTF correction and reconstruction
| Regularized 3D Reconstruction by Shape information
|-  
|-  


| Paper
| Paper
| [[2000DeRosier_EwaldCorrection]]
| [[2012Kucukelbir_adaptiveBasis]]
| CTF correction considering the Ewald sphere
| 3D reconstruction in an adaptive basis promoting sparsity
|-  
|-  


| Paper
| Paper
| [[2000Jensen_TiltedCorrection]]
| [[2012Sindelar_NoiseReduction]]
| CTF correction considering tilt in backprojection
| Optimal noise reduction in 3D reconstructions
|-  
|-  


| Paper
| Paper
| [[2001Saad_CTFEstimate]]
| [[2013Elmlund H_PRIME]]
| CTF estimation
| PRIME: Probabilistic Initial 3D Model Generation for Single-Particle Cryo-Electron Microscopy
|-  
|-  


| Paper
| Paper
| [[2003Huang_CTFEstimate]]
| [[2013Lyumkis_Optimod]]
| CTF estimation
| Construction of initial volumes with Optimod
|-  
|-  


| Paper
| Paper
| [[2003Mindell_CTFTILT]]
| [[2013Wang FIRM]]
| CTF estimation for tilted micrographs
| Fast 3D reconstruction in Fourier domain
|-  
|-  


| Paper
| Paper
| [[2003Sander_MSA]]
| [[2014Kunz_SART_OS]]
| CTF estimation through MSA classification of PSDs
| Simultaneous ART with OS
|-  
|-  


| Paper
| Paper
| [[2003Velazquez_ARMA]]
| [[2015Abrishami_Fourier]]
| PSD and CTF estimation using ARMA models
| 3D Reconstruction in Fourier space
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_IDR]]
| [[2015Dvornek_SubspaceEM]]
| CTF restoration and reconstruction with Iterative Data Refinement
| Fast Maximum a posteriori
|-  
|-  


| Conference
| Paper
| [[2004Wan_CTF]]
| [[2015Moriya_Bayesian]]
| Spatially variant CTF
| Bayesian approach to suppress limited angular artifacts
|-  
|-  


| Paper
| Paper
| [[2004Zubelli_Chahine]]
| [[2015Xu_GeometricFlow]]
| CTF restoration and reconstruction with Chahine's multiplicative method
| Multi-scale geometric flow
|-  
|-  


| Conference
| Arxiv
| [[2005Dubowy_SpaceVariant]]
| [[2016Ye_Cohomology]]
| CTF correction when this is space variant
| Cohomology properties of 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2005Mallick_ACE]]
| [[2017Barnett_Marching]]
| CTF estimation
| Initial volume through frequency marching
|-  
|-  


| Paper
| Paper
| [[2006Wolf_Ewald]]
| [[2017Punjani_CryoSPARC]]
| CTF correction considering Ewald sphere
| CryoSPARC
|-  
|-  


| Paper
| Paper
| [[2007Jonic_EnhancedPSD]]
| [[2017Punjani_CryoSPARCTheory]]
| PSD enhancement for better identification of Thon rings; Vitreous ice diffracts in Thon rings
| Theory related to CryoSPARC
|-  
|-  


| Paper
| Paper
| [[2007Philippsen_Model]]
| [[2017Sorzano_SurveyIterative]]
| CTF Model for tilted specimens
| Survey of iterative reconstruction methods for EM
|-  
|-  


| Paper
| Paper
| [[2007Sorzano_CTF]]
| [[2018Bartesaghi_Refinement]]
| CTF estimation using enhanced PSDs
| Refinement of CTF, frame weight and alignment for high resolution reconstruction
|-  
|-  


| Paper
| Paper
| [[2009Sorzano_Sensitivity]]
| [[2018Hu_ParticleFilter]]
| Error sensitivity of the CTF models, non-uniqueness of the CTF parameters
| A particle filter framework for 3D reconstruction
|-  
|-  


| Paper
| Conference
| [[2010Jiang2010_CTFCorrection]]
| [[2018Levin_Kam]]
| Amplitude correction method
| Ab initio reconstruction by autocorrelation analysis
|-  
|-  


| Paper
| Conference
| [[2010Kasantsev_CTFCorrection]]
| [[2018Michels_RBF]]
| Mathematical foundations of Kornberg and Jensen method
| Ab-initio reconstruction with radial basis functions
|-  
|-  


| Paper
| Paper
| [[2010Leong_CTFCorrection]]
| [[2018Reboul_Simple]]
| Correction for spatially variant CTF
| Ab initio reconstruction with Simple
|-  
|-  


| Paper
| Paper
| [[2011Glaeser_Coma]]
| [[2018Sorzano_Highres]]
| The effect of coma at high-resolution
| New algorithm for 3D Reconstruction and alignment with emphasis on significance
|-  
|-  


| Paper
| Paper
| [[2011Mariani_Tilted]]
| [[2018Sorzano_Swarm]]
| CTF simulation and correction of tilted specimens
| Consensus of several initial volumes by swarm optimization
|-  
|-  


| Paper
| Paper
| [[2011Sindelar_Wiener]]
| [[2018Zhu_Ewald]]
| CTF correction using a modified version of Wiener filter
| 3D Reconstruction with Ewald sphere correction
|-  
|-  


| Paper
| Paper
| [[2011Voortman_Tilted]]
| [[2019Gomez_Initial]]
| CTF correction for tilted specimen
| Construction of initial models
|-  
|-  


| Paper
| Master
| [[2012Voortman_VaryingCTF]]
| [[2019Havelkova_Regularization]]
| Correcting a spatially varying CTF
| Regularization methods in 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2013Vargas_FastDef]]
| [[2019Wilkinson_Scales]]
| Fast defocus
| Combining data acquired at different scales
|-  
|-  


| Paper
| Paper
| [[2014Penczek_CTER]]
| [[2020Alazzawi_Auto]]
| Estimation of the CTF errors
| Automatic full processing of micrographs to yield a 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2015Rohou_CTFFind4]]
| [[2020Pan_TV]]
| CTF Find 4
| 3D Reconstruction with total variation regularization
|-  
|-  


| Paper
| Paper
| [[2015Sheth_CTFquality]]
| [[2020Punjani_NonUniform]]
| Visualization and quality assessment of CTF
| Non-uniform refinement
|-  
|-  


| Paper
| Paper
| [[2016Zhang_GCTF]]
| [[2020Ramlaul_Sidesplitter]]
| gCTF
| Local filtering along the reconstruction iterations
|-  
|-  


| Paper
| Paper
| [[2018Su_GoCTF]]
| [[2020Xie_Automatic]]
| goCTF, CTF for tilted specimens
| Automatic 3D reconstruction from projections
|-
 
| Conference
| [[2020Venkatakrishnan_MBIR]]
| Model based image reconstruction
|-  
|-  


| Paper
| Paper
| [[2020Heimowitz_Aspire]]
| [[2020Zhou_AutomaticSelection]]
| CTF determination in Aspire
| Automatic selection of particles for 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2020Zivanov_HighOrder]]
| [[2021Abrishami_Localized]]
| Estimation of high order aberrations
| Localized reconstruction in scipion expedites the analysis of symmetry mismatches in Cryo-EM data
|-  
|-  


|}
| Paper
| [[2021Gupta_CryoGAN]]
| 3D Reconstruction via Generative Adversarial Learning
|-


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


{|
| Paper
| [[2021Kimanius_PriorKnowledge]]
| Incorporation of prior knowledge during 3D reconstruction
|-


| Paper
| Paper
| [[2006Baker_segmentation]]
| [[2021Sorzano_Uneven]]
| Segmentation of molecular subunits
| Algorithmic robustness to uneven angular distributions
|-  
|-  


| Paper
| Paper
| [[2010Pintilie_segger]]
| [[2022Havelkova_regularization]]
| Segmentation of molecular subunits
| Regularization of iterative reconstruction algorithms
|-  
|-  


| Conference
| Conference
| [[2017Nissenson_VolumeCut]]
| [[2022Kimanius_Sparse]]
| Segmentation of an EM volume using an atomic model
| Sparse Fourier backpropagation
|-  
|-  


| Paper
| Paper
| [[2019Beckers_FDR]]
| [[2022Lan_RCT]]
| Segmentation of the protein using False Discovery Rate
| Random Conical Tilt without picking
|-  
|-  


| Paper
| Paper
| [[2020Beckers_FDR]]
| [[2023Bendory_Autocorrelation]]
| Segmentation of the protein using False Discovery Rate (GUI)
| Initial volume through autocorrelation analysis with sparsity constraints
|-  
|-  


| Paper
| Paper
| [[2020Farkas_MemBlob]]
| [[2023Geva_AbInitio]]
| Segmentation of membrane in membrane embedded proteins
| Initial volume through common lines for tetahedral and octahedral symmetry
|-  
|-  


| Paper
| Paper
| [[2020Terashi_MainMastSeg]]
| [[2023Herreros_ZART]]
| Segmentation of proteins into domains
| Correction of continuous heterogeneity during the 3D reconstruction
|-  
|-  


|}
| Paper
 
| [[2023Rangan_AbInitio]]
=== Fitting and docking ===
| Robust ab initio reconstruction
 
|-
{|


| Paper
| Paper
| [[1999Volkmann_Fitting]]
| [[2023Zhu_CryoSieve]]
| Fitting in real space
| CryoSieve: Selection of the best particles to reconstruct
|-  
|-  


| Paper
| Paper
| [[2001Baker_Review]]
| [[2024Aiyer_Workflow]]
| Review of protein structure prediction
| Workflow for the reconstruction of tilted samples
|-  
|-  


| Paper
| Paper
| [[2001Jones_Review]]
| [[2024Huang_CryoNefen]]
| Review of protein structure prediction
| 3D reconstruction in real space with neural networks
|-  
|-  


| Paper
| Paper
| [[2003Kovacs_FRM3D]]
| [[2024Liu_kinetic]]
| Fast Rotational Alignment of two EM maps
| A kinetic model for the resolution of the initial model using common lines
|-  
|-  


| Paper
| Paper
| [[2004Tama_NMA1]]
| [[2024Suder_Workflow]]
| Flexible fitting with Normal Modes (I)
| Workflow for the reconstruction of subparticles in highly symmetrical objects
|-  
|-  


| Paper
| Paper
| [[2004Tama_NMA2]]
| [[2024Zhu_SIRM]]
| Flexible fitting with Normal Modes (II)
| Reconstruction strategy and weights to fight preferred orientations
|-  
|-  


| Paper
| Paper
| [[2005Velazquez_Superfamilies]]
| [[2025Liu_SpIsonet]]
| Recognition of the superfamily folding in medium-high resolution volumes
| Deep learning approach to fighting preferential orientations during 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2007DeVries_Haddock]]
| [[2025Singh_Mismatch]]
| Docking with Haddock 2.0
| Image processing workflow to address particles with symmetry mismatches
|-  
|-  


| Paper
| Paper
| [[2007Kleywegt_QualityControl]]
| [[2025Van_Probabilistic]]
| Quality control and validation of fitting
| Multireference initial volume reconstruction in SPA
|-  
|-  


| Paper
| Paper
| [[2012Biswas_Secondary]]
| [[2025Woollard_InstaMap]]
| Secondary structure determination in EM volumes
| InstaMap: 3D reconstruction using neural networks
|-  
|-  
|}
=== 3D Heterogeneity ===
{|


| Paper
| Paper
| [[2012Velazquez_Constraints]]
| [[2004White_Size]]
| Multicomponent fitting by using constraints from other information sources
| Heterogeneity classification of differently sized images
|-  
|-  


| Paper
| Paper
| [[2013Chapman MS_Atomicmodeling]]
| [[2006Penczek_Bootstrap]]
| Atomic modeling of cryo-electron microscopy reconstructions--joint refinement of model and imaging parameters
| 3D heterogeneity through bootstrap
|-  
|-  


| Paper
| Paper
| [[2013Esquivel_Modelling]]
| [[2007Leschziner_Review]]
| Review on modelling (secondary structure, fitting, ...)
| Review of 3D heterogeneity handling algorithms
|-  
|-  


| Paper
| Paper
| [[2013Lopez_Imodfit]]
| [[2007Scheres_ML3D]]
| Fitting based on vibrational analysis
| Maximum Likelihood alignment and classification in 3D
|-  
|-  


| Paper
| Paper
| [[2013Nogales_3DEMLoupe]]
| [[2008Herman_Graph]]
| Normal Mode Analysis of reconstructed volumes
| Classification by graph partitioning
|-  
|-  


| Paper
| Paper
| [[2014AlNasr_Secondary]]
| [[2009Spahn_Bootstrap]]
| Identification of secondary structure elements in EM volumes
| 3D heterogeneity through bootstrap
|-  
|-  


| Paper
| Paper
| [[2014Politis_MassSpect]]
| [[2010Elmlund_AbInitio]]
| Integration of mass spectroscopy information
| Solving the initial volume problem with multiple conformations
|-  
|-  


| Paper
| Paper
| [[2014Rey_MassSpect]]
| [[2010Shatsky_MultiVariate]]
| Integration of mass spectroscopy information
| Multivariate Statistical Analysis
|-  
|-  


| Paper
| Paper
| [[2014Villa_Review]]
| [[2012Scheres_Bayesian]]
| Review of atomic fitting into EM volumes
| A Bayesian view on cryo-EM structure determination
|-  
|-  


| Paper
| Paper
| [[2015Barad_EMRinger]]
| [[2012Zheng_Covariance]]
| Validation of hybrid models
| Estimation of the volume covariance
|-  
|-  


| Paper
| Paper
| [[2015Bettadapura_PF2Fit]]
| [[2013Wang_MLVariance]]
| Fast rigid fitting of PDBs into EM maps
| Maximum Likelihood estimate of the map variance
|-  
|-  


| Paper
| Paper
| [[2015Carrillo_CapsidMaps]]
| [[2013Lyumkis D_FREALIGN]]
| Analysis of virus capsids using Google Maps
| Likelihood-based classification of cryo-EM images using FREALIGN.
|-  
|-


| Paper
| Paper
| [[2015Hanson_Continuum]]
| [[2014Chen_Migration]]
| Modelling assemblies with continuum mechanics
| Particle migration analysis in 3D classification
|-  
|-  


| Paper
| Paper
| [[2015Lopez_Review]]
| [[2014Dashti_Brownian]]
| Review of structural modelling from EM data
| Continuous heterogeneity through Brownian trajectories
|-  
|-  


| Paper
| Paper
| [[2015Schroeder_Hybrid]]
| [[2014Schwander_manifold]]
| Review on model building
| Continuous heterogeneity through Manifold Analysis
|-  
|-  


| Paper
| Paper
| [[2015Tamo_Dynamics]]
| [[2014Jin_NMA]]
| Dynamics in integrative modeling
| HEMNMA: Continuous heterogeneity through Normal Mode Analysis
|-  
|-  


| Paper
| Paper
| [[2015Sorzano_AtomsToVoxels]]
| [[2015Anden_Covariance]]
| Accurate conversion of an atomic model into a voxel density volume
| 3D Covariance matrix estimation for heterogeneity
|-  
|-  


| Paper
| Paper
| [[2016Joseph_Evolution]]
| [[2015Bai_Focused]]
| Evolutionary constraints for the fitting of atomic models into density maps
| Focused classification
|-  
|-  


| Paper
| Paper
| [[2016Joseph_Refinement]]
| [[2015Katsevich_Covariance]]
| Refinement of atomic models in high-resolution EM reconstructions using Flex-EM
| 3D Covariance matrix estimation for heterogeneity
|-  
|-  


| Paper
| Paper
| [[2016Murshudov_Refinement]]
| [[2015Klaholz_MRA]]
| Refinement of atomic models in high-resolution EM reconstructions
| Multivariate Statistical Analysis of Jackknife and Bootstrapping on random subsets
|-  
|-  


| Paper
| Paper
| [[2016Segura_3Diana]]
| [[2015Liao_Covariance]]
| Validation of hybrid models
| Estimation of the 3D covariance from 2D projections
|-  
|-  


| Paper
| Paper
| [[2016Singharoy_MDFF]]
| [[2015Tagare_Direct]]
| Construction of hybrid models driven by EM density and molecular dynamics
| Direct reconstruction of PCA components
|-  
|-  


| Paper
| Paper
| [[2016Wang_Rosetta]]
| [[2016Gong_Mechanical]]
| Construction of hybrid models driven by EM density using Rosetta
| Mechanical model for macromolecules
|-  
|-  


| Paper
| Paper
| [[2017Chen_CoarseGraining]]
| [[2016Rawson_Movement]]
| Coarse graining of EM volumes
| Movement and flexibility
|-  
|-  


| Paper
| Paper
| [[2017Joseph_Metrics]]
| [[2016Shan_Multibody]]
| Metrics analysis for the comparison of structures
| Multibody refinement
|-  
|-  


| Paper
| Paper
| [[2017Hryc_WeightedAtoms]]
| [[2016Sorzano_StructMap]]
| Construction of hybrid models by locally weighting the different atoms
| Sorting a discrete set of conformational states
|-  
|-  


| Paper
| Paper
| [[2017Matsumoto_Distribution]]
| [[2016Sorzano_Strain]]
| Estimating the distribution of conformations of atomic models
| Calculate local stretches, strains and rotations from two conformational states
|-  
|-  


| Paper
| Paper
| [[2017Michel_ContactPrediction]]
| [[2017Punjani_CryoSPARC]]
| Structure prediction by contact prediction
| CryoSPARC
|-  
|-  


| Paper
| Paper
| [[2017Miyashita_EnsembleFitting]]
| [[2017Schillbach_Warpcraft]]
| Ensemble fitting using Molecular Dynamics
| Warpcraft: 3D Reconstruction in the presence of continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2017Turk_ModelBuilding]]
| [[2018Anden_Covariance]]
| Tutorial on model building and protein visualization
| Structural Variability from Noisy Tomographic Projections
|-  
|-  


| Paper
| Paper
| [[2017Wang_PartialCharges]]
| [[2018Haselbach_FreeEnergy]]
| Appearance of partial charges in EM maps
| Analysis of the free energy landscape through PCA
|-  
|-  


| Paper
| Paper
| [[2017Wlodawer]]
| [[2018Nakane_MultiBody]]
| Comparison of X-ray and EM high resolution structures
| Structural Variability through multi-body refinement
|-  
|-  


| Paper
| Paper
| [[2018Cassidy_review]]
| [[2019Serna_Review]]
| Review of methods for hybrid modeling
| Review of classification tools
|-  
|-  


| Paper
| Paper
| [[2018Chen_SudeChains]]
| [[2018Solernou_FFEA]]
| A comparison of side chains between X-ray and EM maps
| Fluctuating Finite Element Analysis, continuum approach to Molecular Dynamics
|-  
|-  


| Paper
| Paper
| [[2018Kawabata_Pseudoatoms]]
| [[2019Sorzano_Review]]
| Modelling the EM map with Gaussian pseudoatoms
| Review of continuous heterogeneity biophysics
|-  
|-  


| Paper
| Paper
| [[2018Kovacs_Medium]]
| [[2019Zhang_Local]]
| Modelling of medium resolution EM maps
| Local variability and covariance
|-  
|-  


| Paper
| Paper
| [[2018Neumann_validation]]
| [[2020Dashti_Landscape]]
| Validation of fitting, resolution assessment and quality of fit
| Retrieving functional pathways from single particle snapshots
|-  
|-  


| Paper
| Conference
| [[2018Terwilliger_map_to_model]]
| [[2020Gupta_MultiCryoGAN]]
| Phenix map_to_model, automatic modelling of EM volumes
| Reconstruction of continuously heterogeneous structures with adversarial networks
|-  
|-  


| Paper
| Paper
| [[2018Wang_MD]]
| [[2020Harastani_NMA]]
| Constructing atomic models using molecular dynamics
| HEMNMA in Scipion : Using HEMNMA for analyzing continuous heterogeneity with normal modes
|-  
|-  


| Paper
| Paper
| [[2018Xia_MVPENM]]
| [[2020Maji_Propagation]]
| Multiscale Normal Mode Analysis
| Propagation of conformational coordinates across angular space
|-  
|-  


| Paper
| Paper
| [[2018Yu_Atomic]]
| [[2020Moscovich_DiffusionMaps]]
| Constructing atomic models using existing tools
| Heterogeneity analysis by diffusion maps and spectral volumes
|-  
|-  


| Paper
| Paper
| [[2019Bonomi_Multiscale]]
| [[2020Seitz_Polaris]]
| Bayesian multi-scale modelling
| Analysis of energy landscapes to find minimal action paths
|-  
|-  


| Paper
| Conference
| [[2019Klaholz_Review]]
| [[2020Zhong_CryoDRGN]]
| Review of Phenix tools to modelling
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
|-  
|-  


| Paper
| Paper
| [[2019Subramaniya_DeepSSE]]
| [[2020Verbeke_Separation]]
| Secondary structure prediction from maps using deep learning
| Heterogeneity analysis by comparing common lines
|-  
|-  


| Paper
| Paper
| [[2019Zhang_CoarseGrained]]
| [[2021Chen_GM]]
| Coarse-graining of EM maps
| Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability
|-  
|-  


| Paper
| Paper
| [[2020Costa_MDeNM]]
| [[2021Giraldo_cryoBIFE]]
| Flexible fitting with molecular dynamics and normal modes
| A Bayesian approach to extracting free‑energy profiles
|-  
|-  


| Paper
| Conference
| [[2020Cragnolini_Tempy2]]
| [[2021Hamitouche_NMADL]]
| TEMpy2 library for density-fitting and validation
| Continuous heterogeneity analysis through normal modes and deep learning
|-  
|-  


| Paper
| Paper
| [[2020Dodd_ModelBuilding]]
| [[2021Herreros_Zernikes3D]]
| Model building possibilities, with special emphasis on flexible fitting
| Continuous heterogeneity analysis through Zernikes 3D
|-  
|-  


| Paper
| Paper
| [[2020Ho_CryoID]]
| [[2021Kazemi_Enrich]]
| Identification of proteins in structural proteomics from cryoEM volumes
| ENRICH: A fast method to improve the quality of flexible macromolecular reconstructions
|-  
|-  


| Paper
| Paper
| [[2020Hoh_Buccaneer]]
| [[2021Matsumoto_DEFmap]]
| Structure modelling with Buccaneer
| Prediction of RMSF of Molecular Dynamics from a CryoEM map using deep learning
|-  
|-  


| Chapter
| [[2021Nakasako_Landscape]]
| Estimation of free-energy landscape from images
|-


| Paper
| Paper
| [[2020Joseph_comparison]]
| [[2021Punjani_3DVA]]
| Comparison of map and model, or two maps
| 3D Variability analysis from images
|-  
|-  


| Paper
| Paper
| [[2020Kim_Review]]
| [[2021Sorzano_PCA]]
| Review of the options for atomic modelling
| PCA is limited to low-resolution
|-  
|-  


| Paper
| Paper
| [[2020Leelananda_Constraints]]
| [[2021Zhong_CryoDRGN]]
| NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD structure refinement
| CryoDRGN to analyze the continuous heterogeneity by CryoEM
|-  
|-  


| Paper
| Paper
| [[2020Liebschner_Ceres]]
| [[2022Arnold_liganded]]
| CERES: Web server of refined atomic maps of CryoEM deposited maps by Phenix
| Test to see if liganded states can be detected
|-  
|-  


| Paper
| Paper
| [[2020Vant_Flexible]]
| [[2022Ecoffet_MorphOT]]
| Flexible fitting with molecular dynamics and neural network potentials
| More physically plausible morphing between two states
|-  
|-  


| Paper
| Paper
| [[2021Lawson_Challenge]]
| [[2022Gomez_Hierarchical]]
| Validation recommendations based on outcomes of the 2019 EMDataResource challenge
| Hierarchical classification of particles
|-  
|-  


| Paper
| Paper
| [[2021Saltzberg_IMP]]
| [[2022Hamitouche_DeepHEMNMA]]
| Using the Integrative Modeling Platform to model a cryoEM map
| DeepHEMNMA: Continuous heterogeneity analysis through normal modes and deep learning
|-  
|-  


|}
| Conference
| [[2022Levy_CryoFire]]
| CryoFire: heterogeneity and alignment through amortized inference
|-


=== Books and reviews ===
| Paper
| [[2022Rabuck_Quant]]
| Workflow for discrete heterogeneity analysis
|-


{|
| Paper
| [[2022Seitz_ESPER]]
| ESPER through manifold embeddings
|-


| Book
| Paper
| [[1980Herman_Tomography]]
| [[2022Skalidis_Endogenous]]
| General book on tomography
| AI tools to recognize proteins in cellular fractions
|-  
|-  


| Book
| Paper
| [[1988Kak_Tomography]]
| [[2022Wu_Manifold]]
| General book on tomography
| Continuous heterogeneity through manifold learning
|-  
|-  


| Paper
| Paper
| [[2000Tao_Review]]
| [[2022Zhou_Data]]
| Review of single particles
| Determination of the number of discrete 3D classes
|-  
|-  


| Paper
| Paper
| [[2000VanHeel_Review]]
| [[2023Barchet_Focused]]
| Review of single particles
| Applications and strategies in focused classification and refinement
|-  
|-  


| Paper
| Paper
| [[2002Frank_Review]]
| [[2023Afonine_Varref]]
| Review of single particles
| Phenix.varref for the analysis of the model heterogeneity
|-  
|-  


| Paper
| Paper
| [[2002Schmid_Review]]
| [[2023Chen_GMM]]
| Review of single particles
| Continuous heterogeneity analysis with GMMs and neural networks
|-  
|-  


| Paper
| Paper
| [[2004Henderson_Review]]
| [[2023Dsouza_benchmark]]
| Review of electron microscopy
| Benchmark analysis of various continuous heterogeneity algorithms
|-  
|-  


| Paper
| Paper
| [[2004Subramaniam_Review]]
| [[2023Esteve_Spectral]]
| Review of single particles
| Continuous heterogeneity analysis through the spectral decomposition of the atomic structure
|-  
|-  


| Paper
| Paper
| [[2005Steven_Review]]
| [[2023Fernandez_Subtraction]]
| Review of electron microscopy
| Subtraction of unwanted signals to improve classification and alignment
|-  
|-  


| Paper
| Paper
| [[2006Fernandez_Review]]
| [[2023Forsberg_Filter]]
| Review of electron microscopy
| Filter to estimate the local heterogeneity
|-  
|-  


| Book
| Paper
| [[2006Frank_book]]
| [[2023Herreros_Hub]]
| Book covering all aspects of electron microscopy of single particles
| Flexibility hub: an integrative platform for continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2006Sorzano_Review]]
| [[2023Luo_OpusDSD]]
| Review of optimization problems in electron microscopy
| OPUS DSD: a neural network approach to continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2007Leschziner_Review]]
| [[2023Kinman_Analysis]]
| Review of 3D heterogeneity handling algorithms
| Analysis of the continuous heterogeneity results of CryoDrgn
|-  
|-  


| Paper
| Paper
| [[2007Sorzano_Review]]
| [[2023Matsumoto_DEFmap]]
| Review of the image processing steps
| Quantitative analysis of the prediction of RMSF from a map using DefMap
|-  
|-  


| Paper
| Paper
| [[2008Fanelli_ImageFormation]]
| [[2023Punjani_3DFlex]]
| Review on the image formation model from the electron waves and open inverse-problems in Electron Tomography
| Continuous heterogeneity through 3DFlex
|-  
|-  


| Paper
| Paper
| [[2008Fernandez_HPCReview]]
| [[2023Seitz_Geometric]]
| High performance computing in electron cryomicroscopy
| Geometric relationships between manifold embeddings of a continuum of 3D molecular structures and their 2D projections
|-  
|-  


| Paper
| Paper
| [[2008Jonic_Review]]
| [[2023Seitz_ESPER]]
| Comparison between electron tomography and single particles
| Continuous heterogeneity through Embedded subspace partitioning and eigenfunction realignment
|-  
|-  


| Paper
| Paper
| [[2008Mueller_Review]]
| [[2023Tang_Reweighting]]
| Review of Electron microscopy
| Ensemble reweighting using Cryo-EM particles
|-  
|-  


| Paper
| Paper
| [[2008Taylor_Review]]
| [[2023Vuillemot_MDSPACE]]
| Review of Electron microscopy
| MDSPACE: Continuous heterogeneity analysis through normal modes and MD simulation
|-  
|-  


| Paper
| Paper
| [[2010DeRosier_Review]]
| [[2023Wang_Autoencoder]]
| Personal account of how 3DEM developed in the early days
| Discrete heterogeneity based on autoencoders
|-  
|-  


| Chapter
| Paper
| [[2012Sorzano_Review]]
| [[2024Amisaki_Multilevel]]
| Review of single particle analysis using Xmipp
| Multilevel PCA for the analysis of hierarchical continuous heterogeneity
|-  
|-  


| Chapter
| Paper
| [[2012Devaux_Protocol]]
| [[2024Chen_Focused]]
| Protocols for performing single particle analysis
| Focused reconstruction of heterogeneous macromolecules
|-  
|-  


| Paper
| Paper
| [[2014Bai_Review]]
| [[2024Fan_CryoTrans]]
| Recent advances in cryo-EM
| CryoTrans: Trajectory generation between two states
|-  
|-  


| Paper
| Paper
| [[2015Carazo_Review]]
| [[2024Klindt_Disentanglement]]
| Review of the reconstruction process
| 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
| [[2015Cheng_Review]]
| [[2024Li_CryoStar]]
| A primer to Single Particle Cryo-EM
| CryoStar: Continuous heterogeneity analysis with structural priors
|-  
|-  


| Paper
| Paper
| [[2015Cheng_Reviewb]]
| [[2024Schwab_DynaMight]]
| Single Particle Cryo-EM at crystallographic resolution
| DynaMight: Heterogeneity analysis using neural networks
|-  
|-  


| Paper
| Paper
| [[2015Elmlund_Review]]
| [[2024Shi_Priors]]
| Recent advances in cryo-EM
| Latent space priors for continuous heterogeneity
|-  
|-  


| Paper
| Paper
| [[2015Henderson_Review]]
| [[2024Song_RMSFNet]]
| Recent advances in cryo-EM
| RMSFNet: prediction of Molecular Dynamics RMSF from the cryoEM map
|-  
|-  


| Paper
| Paper
| [[2015Nogales_Review]]
| [[2024Yoshidome_4D]]
| Recent advances in cryo-EM
| Heterogeneity analysis using molecular dynamics
|-  
|-  


| Paper
| Paper
| [[2015Schroeder_Review]]
| [[2025Chen_GMM]]
| Review of advances in the electron microscope
| Continuous heterogeneity analysis in SPA using atomic models
|-  
|-  


| Paper
| Paper
| [[2015VanDenBedem_Integrative]]
| [[2025Dingeldein]]
| Review of integrative structural biology
| Amortized template matching using simulation-based inference
|-  
|-  


| Paper
| Paper
| [[2015Wu_Review]]
| [[2025Herreros_HetSiren]]
| Review of advances in cryo-EM
| Discrete and Continuous heterogeneity analysis using neural networks
|-  
|-  


| Paper
| Paper
| [[2016Carroni_CryoEM]]
| [[2025Gilles_Covariance]]
| Review of advances in Cryo-EM
| Continuous heterogeneity analysis using regularized covariance estimation and kernel regression
|-  
|-  


| Paper
| Paper
| [[2016Egelman_CryoEM]]
| [[2025Kinman_SIREN]]
| Review of advances in Cryo-EM
| Heterogeneity analysis using coocurrence analysis (SIREN)
|-  
|-  


| Paper
| Paper
| [[2016Eisenstein_CryoEM]]
| [[2025Lauzirika_Distinguishable]]
| News feature on the Method of the Year
| How many (distinguishable) classes can we identify in single-particle analysis?
|-  
|-  


| Paper
| Paper
| [[2016FernandezLeiro_Review]]
| [[2025Levy_CryoDRGNAI]]
| Review of EM
| CryoDRGN-AI: Heterogeneity analysis and ab initio 3D reconstruction for SPA and STA
|-  
|-  
|}
=== Validation ===
{|


| Paper
| Paper
| [[2016Glaeser_HowGood]]
| [[2008Stagg_TestBed]]
| How good can cryo-EM become?
| Effect of voltage, dosis, number of particles and Euler jumps on resolution
|-  
|-  


| Paper
| Paper
| [[2016Jonic_PseudoAtoms]]
| [[2011Henderson]]
| Review of the applications of the use of pseudoatoms in EM
| Tilt Validation
|-  
|-  


| Chapter
| Paper
| [[2016Mio_Review]]
| [[2011Read]]
| Overview of the process to obtain EM reconstructions
| Validation of PDBs
|-  
|-  


| Paper
| Paper
| [[2016Jonic_Review]]
| [[2012Henderson]]
| A review of computational ways to handle heterogeneity
| EM Map Validation
|-  
|-  


| Paper
| Paper
| [[2016Nogales_Review]]
| [[2013Cossio_Bayesian]]
| Review of advances in cryo-EM
| EM Map Validation in a probabilistic setting
|-  
|-  


| Paper
| Paper
| [[2016Subramaniam_Review]]
| [[2013Chen_NoiseSubstitution]]
| Why cryo-EM is now suitable for crystallographic journals
| Noise substitution at high resolution for measuring overfitting
|-  
|-  


| Paper
| Paper
| [[2016Vinothkumar_Review]]
| [[2013Ludtke_Validation]]
| Historical review and current limitations
| Structural validation, example of the Calcium release channel
|-  
|-  


| Report
| Paper
| [[2017Brezinski_Nobel]]
| [[2013Murray_Validation]]
| Scientific background on the Nobel Prize in Chemistry 2017
| Validation of a 3DEM structure through a particular example
|-  
|-  


| Paper
| Paper
| [[2017Cheng_review]]
| [[2014Russo_StatisticalSignificance]]
| Why CryoEM became so hot
| EM Map Validation through the statistical significance of the tilt-pair angular assignment
|-  
|-  


| Paper
| Paper
| [[2017Danev_Review]]
| [[2014Stagg_Reslog]]
| Review of the use of phase plates in EM
| EM Map Validation through the resolution evolution with the number of particles
|-  
|-  


| Paper
| Paper
| [[2017Elmlund_Review]]
| [[2014Wasilewski_Tilt]]
| Review of the main current difficulties of EM
| Web implementation of the tilt pair validation
|-  
|-  


| Paper
| Paper
| [[2017Frank_Review]]
| [[2015Heymann_Alignability]]
| Historical review of EM
| EM Map Validation through the resolution of reconstructions from particles and noise
|-  
|-  


| Paper
| Paper
| [[2017Frank_TimeResolved]]
| [[2015Oliveira_FreqLimited]]
| Review of time-resolved of EM
| Comparison of gold standard and frequency limited optimization
|-  
|-  


| Paper
| Paper
| [[2017Jonic_Review]]
| [[2015Rosenthal_Review]]
| Review of computational methods to analyze conformational variability
| Review of validation methods
|-  
|-  


| Paper
| Paper
| [[2017Merino_DrugEM]]
| [[2015Wriggers_Secondary]]
| Applications of EM for drug design
| Validation by secondary structure
|-  
|-  


| Paper
| Paper
| [[2017Rawson_Limitations]]
| [[2016Degiacomi_IM]]
| Limitations of EM for drug design
| Comparison of Ion Mobility data and EM volumes
|-  
|-  


| Paper
| Paper
| [[2017Sorzano_FourierProperties]]
| [[2016Kim_SAXS]]
| Review of statistical properties of resolution measures defined in Fourier space
| Comparison of SAXS data and EM projections
|-  
|-  


| Paper
| Paper
| [[2017Sorzano_SurveyIterative]]
| [[2016Rosenthal_Review]]
| Survey of iterative reconstruction methods for EM
| Review of validation methods
|-  
|-  


| Paper
| Paper
| [[2018Bruggeman_Crowdsourcing]]
| [[2016Vargas_Alignability]]
| Exploring crowdsourcing for EM image processing
| Validation by studying the tendency of an angular assignment to cluster in the projection space
|-  
|-  


| Paper
| Paper
| [[2018Cheng_Review]]
| [[2017Monroe_PDBRefinement]]
| Review of EM and future ahead
| Validation by comparison to a refined PDB
|-  
|-  


| Paper
| Paper
| [[2018Cossio_ML]]
| [[2018Afonine_Phenix]]
| Review of Maximum Likelihood methods
| Tools in Phenix for the validation of EM maps
|-  
|-  


| Paper
| Paper
| [[2018Grimes_Crystallography]]
| [[2018Heymann_Bsoft]]
| Review of X-ray crystallography and its relationship to EM
| Map validation using Bsoft
|-  
|-  


| Paper
| Paper
| [[2018Murata_Review]]
| [[2018Heymann_Challenge]]
| Review of EM for structure dynamics
| A summary of the assessments of the 3D Map Challenge
|-  
|-  


| Paper
| Paper
| [[2018Quentin_Biomedical]]
| [[2018Jonic_Gaussian]]
| Review of EM as a tool for biomedical research
| Assessment of sets of volumes by pseudoatomic structures
|-  
|-  


| Paper
| Paper
| [[2018Scapin_DrugDiscovery]]
| [[2018Naydenova_AngularDistribution]]
| Review of EM as a tool for drug discovery
| Evaluating the angular distribution of a 3D reconstruction
|-  
|-  


| Paper
| Paper
| [[2018Vilas_ImageProcessing]]
| [[2018Pages_Symmetry]]
| Review of the recent developments in image processing for single particle analysis
| Looking for a symmetry axis in a PDB
|-  
|-  


| Paper
| Paper
| [[2018vonLoeffelholz_VPP]]
| [[2018Pintilie_SSE]]
| Comparison of Volta Phase Plate reconstructions close to focus and with defocus
| Evaluating the quality of SSE and side chains
|-  
|-  


| Paper
| Paper
| [[2018Eisenstein_DrugDesigners]]
| [[2019Herzik_Multimodel]]
| Drug designers embrace cryo-EM
| Local and global quality by multi-model fitting
|-  
|-  


| Paper
| Paper
| [[2019Benjin_Review]]
| [[2020Chen_Atomic]]
| Review of SPA
| Validation of the atomic models derived from CryoEM
|-  
|-  


| Paper
| Paper
| [[2019Danev_Review]]
| [[2020Cossio_CrossValidation]]
| Review of future directions
| Need for cross validation
|-  
|-  


| Paper
| Paper
| [[2019Lyumkis_Review]]
| [[2020Ortiz_CrossValidation]]
| Challenges and reviews
| Cross validation for SPA
|-  
|-  


| Paper
| Paper
| [[2019Sorzano_Review]]
| [[2020Sazzed_helices]]
| Review of continuous heterogeneity biophysics
| Validation of helix quality
|-  
|-  


| Paper
| Paper
| [[2020Abriata_Review]]
| [[2020Stojkovic_PTM]]
| Considerations of structure prediction and CryoEM
| Validation of post-translational modifications
|-  
|-  


| Paper
| Paper
| [[2020Akbar_Review]]
| [[2020Tiwari_PixelSize]]
| Review of membrane protein reconstructions
| Fine determination of the pixel size
|-  
|-  


| Paper
| Paper
| [[2020Bendory_Review]]
| [[2021Mendez_Graph]]
| Review of image processing problems
| Identification of incorrectly oriented particles
|-  
|-  


| Paper
| Paper
| [[2020Dubach_Review]]
| [[2021Pintilie_Validation]]
| Review of resolution in X-ray crystallography and CryoEM
| Review of map validation approaches
|-  
|-  


| TechReport
| Paper
| [[2020Lai_Statistics]]
| [[2021Olek_FDR]]
| Review of statistical properties of image alignment
| Cryo-EM Map–Based Model Validation Using the False Discovery Rate Approach
|-  
|-  


| Paper
| Paper
| [[2020McCafferty_Review]]
| [[2022Garcia_DeepHand]]
| Review of SPA and Mass Spectroscopy
| Checking the correct handedness with a neural network
|-  
|-  


| Paper
| Paper
| [[2020Seffernick_Hybrid]]
| [[2022Sorzano_Bias]]
| Review of hybrid (computational and experimental) methods to get protein structure
| Bias, variance, gold-standard and overfitting in SPA
|-  
|-  


| Paper
| Paper
| [[2020Vilas_Review]]
| [[2022Sorzano_Validation]]
| Review of local resolution
| Validation scheme and server for SPA
|-  
|-  


| Paper
| Paper
| [[2020Wu_Review]]
| [[2022Terashi_DAQ]]
| Review of current limitations, with special emphasis on protein size
| Validation of models fitted into CryoEM maps
|-  
|-  


| Paper
| Paper
| [[2020Singer_Sigworth_Review]]
| [[2022Waarshamanage_EMDA]]
| Review of single particle analysis
| Validation of models fitted into CryoEM maps
|-
|-  
 
|}
 
=== Software ===
 
{|


| Paper
| Paper
| [[1996Frank_Spider]]
| [[2024Feng_DeepQs]]
| Spider
| DeepQ: Local quality of the map
|-  
|-  


| Paper
| Paper
| [[1996VanHeel_Imagic]]
| [[2024Jeon_CryoBench]]
| Imagic
| Datasets for heterogeneity benchmarking
|-  
|-  


| Paper
| Paper
| [[1999Lutdke_Eman]]
| [[2024Lytje_SAXS]]
| Eman
| Validation of CryoEM maps with SAXS curves
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2024Sanchez_Anisotropy]]
| Xmipp
| New measure of anisotropy in maps
|-  
|-  


| Paper
| Paper
| [[2007Baldwin_AngularTransformations]]
| [[2024Verbeke_SelfFSC]]
| The Transform Class in SPARX and EMAN2
| Self FSC: FSC with a single map
|-  
|-  


| Paper
| Paper
| [[2007Heymann_Bsoft]]
| [[2025Bromberg_Hand]]
| Bsoft
| Handedness validation based on the Ewald sphere
|-  
|-  


| Paper
| Paper
| [[2007Grigorieff_Frealign]]
| [[2025Pintilie_QScore]]
| Frealign
| Extension of Q-Score to analyze SPA maps
|-  
|-  
|}
=== Resolution ===
{|


| Paper
| Paper
| [[2008Scheres_XmippProtocols]]
| [[1986Harauz_FBP]]
| Xmipp Protocols
| Fourier Shell Correlation
|-  
|-  


| Paper
| Paper
| [[2008Shaikh_SpiderProtocols]]
| [[1987Unser_SSNR]]
| Spider Protocols
| 2D Spectral Signal to Noise Ratio
|-  
|-  


| Paper
| Paper
| [[2012Wriggers_SitusConventions]]
| [[2002Penczek_SSNR]]
| Conventions and workflows in Situs
| 3D Spectral Signal to Noise Ratio for Fourier based algorithms
|-  
|-  


| Paper
| Paper
| [[2013DeLaRosa_Xmipp30]]
| [[2003Rosenthal_DPR]]
| Xmipp 3.0
| Review of the FSC and establishment of a new threshold
|-  
|-  


| Paper
| Paper
| [[2015Cianfrocco_Cloud]]
| [[2005Unser_SSNR]]
| Software execution in the cloud
| 3D Spectral Signal to Noise Ratio for any kind of algorithms
|-  
|-  


| Paper
| Paper
| [[2015Cheng_MRC2014]]
| [[2005VanHeel_FSC]]
| Extensions to MRC file format
| Establishment of a new threshold for FSC
|-  
|-  


| Paper
| Paper
| [[2013DeLaRosa_Scipion]]
| [[2007Sousa_AbInitio]]
| Scipion
| Resolution measurement on neighbour Fourier voxels
|-  
|-  


| Paper
| Paper
| [[2016Scheres_Relion]]
| [[2014Kucukelbir_Local]]
| Tutorial on the use of Relion
| Quantifying the local resolution of cryo-EM density maps
|-  
|-  


| Paper
| Paper
| [[2016Grigorieff_Frealign]]
| [[2016Pintilie_Probabilistic]]
| Tutorial on the use of Frealign
| Probabilistic models and resolution
|-  
|-  


| Paper
| Paper
| [[2017Moriya_Sphire]]
| [[2017Sorzano_FourierProperties]]
| Tutorial on the use of Sphire
| Statistical properties of resolution measures defined in Fourier space
|-  
|-  


| Paper
| Conference
| [[2018Bell_EMAN2]]
| [[2018Avramov_DeepLearning]]
| New tools in EMAN2
| Deep learning classification of volumes into low, medium and high resolution
|-  
|-  


| Paper
| Paper
| [[2018Cianfrocco_cloud]]
| [[2018Carugo_BFactors]]
| CryoEM Cloud Tools
| How large can B-factors be in protein crystals
|-  
|-  


| Paper
| Conference
| [[2018Grant_cisTEM]]
| [[2018Kim_FourierError]]
| cisTEM
| Comparison between a gold standard and a reconstruction
|-  
|-  


| Paper
| Paper
| [[2018McLeod_MRCZ]]
| [[2018Rupp_Problems]]
| MRC Compression format
| Problems of resolution as a proxy number for map quality
|-  
|-  


| Paper
| Paper
| [[2018Zivanov_Relion3]]
| [[2018Vilas_MonoRes]]
| Relion 3
| Local resolution by monogenic signals
|-  
|-  


| Paper
| Paper
| [[2020Caesar_Simple3]]
| [[2018Yang_Multiscale]]
| Simple 3
| Resolution from a multiscale spectral analysis
|-  
|-  
|}
== Electron tomography ==
=== Image preprocessing ===
{|


| Paper
| Paper
| [[2015Yan_thickness]]
| [[2019Avramov_DeepLearning]]
| Determination of thickness, tilt and electron mean free path
| Deep learning classification of volumes into low, medium and high resolution
|-  
|-  


| Paper
| Paper
| [[2018Wu_contrast]]
| [[2019Heymann_Statistics]]
| Contrast enhancement to improve alignability
| SNR, FSC, and related statistics
|-  
|-  
|}
=== Image alignment ===
{|


| Paper
| Paper
| [[1982Guckenberger_commonOrigin]]
| [[2019Ramirez_DeepRes]]
| Determination of a common origin in the micrographs of titl series in three-dimensional electron microscopy
| Resolution determination by deep learning
|-  
|-  


| Paper
| Paper
| [[1992Lawrence_leastSquares]]
| [[2020Baldwin_Lyumkis_SCF]]
| Least squares solution of the alignment problem
| Resolution attenuation through non-uniform Fourier sampling
|-  
|-  


| Paper
| Paper
| [[1995Penczek_dual]]
| [[2020Beckers_Permutation]]
| Dual tilt alignment
| Permutation tests for the FSC
|-  
|-  


| Paper
| Paper
| [[1996Owen_alignmentQuality]]
| [[2020Penczek_mFSC]]
| Automatic alignment without fiducial markers and evaluation of alignment quality
| Modified FSC to avoid mask induced artifacts
|-  
|-  


| Paper
| Paper
| [[1998Grimm_normalization]]
| [[2020Vilas_MonoDir]]
| Discussion of several gray level normalization methods for electron tomography
| Local and directional resolution
|-  
|-  


| Paper
| Paper
| [[2001Brandt_Automatic1]]
| [[2023Dai_CryoRes]]
| Automatic alignment without fiducial markers
| Local resolution through deep learning
|-  
|-  


| Paper
| Paper
| [[2001Brandt_Automatic2]]
| [[2023Vilas_FSO]]
| Automatic alignment with fiducial markers
| Fourier Shell Occupancy to measure anisotropy
|-  
|-  


| Paper
| Paper
| [[2006Winkler_alignment]]
| [[2025Urzhumtsev_RescaleFSC]]
| Marker-free alignment and refinement
| Rescaling of the FSC
|-  
|-  


| Paper
|}
| [[2006Castano_alignment]]
| Alignment with non-perpendicularity
|-


=== Sharpening of high resolution information ===
{|
| Paper
| Paper
| [[2007Castano_alignment]]
| [[2003Rosenthal_DPR]]
| Fiducial-less alignment of cryo-sections
| Contrast restoration and map sharpening
|-  
|-  


| Paper
| Paper
| [[2009Sorzano_alignment]]
| [[2008Fernandez_Bfactor]]
| Marker-free alignment and refinement
| Bfactor determination and restoration
|-  
|-  


| Paper
| Paper
| [[2010Cantele_dualAlignment]]
| [[2013Fiddy_SaxtonAlgorithm]]
| Alignment of dual series
| Phase retrieval or extension
|-  
|-  


| Paper
| Paper
| [[2014Tomonaga_Automatic]]
| [[2014Kishchenko_SphericalDeconvolution]]
| Automatic alignment of tilt series using the projection themselves
| Spherical deconvolution
|-  
|-  


| Paper
| Paper
| [[2014Han_Automatic]]
| [[2015Spiegel_VISDEM]]
| Automatic alignment of tilt series using SIFT features
| Visualization improvement by the use of pseudoatomic profiles
|-  
|-  


| Paper
| Paper
| [[2015Han_Automatic]]
| [[2016Jonic_Pseudoatoms]]
| Automatic alignment of tilt series using fiducials
| Approximation with pseudoatoms
|-  
|-  


| Paper
| Paper
| [[2017Mastronarde_Automatic]]
| [[2016Jonic_Denoising]]
| Automatic alignment and reconstruction of tilt series in IMOD
| Denoising and high-frequency boosting by pseudoatom approximation
|-  
|-  


| Paper
| Paper
| [[2018Fernadez_Beam]]
| [[2017Jakobi_LocScale]]
| Image alignment considering beam induced motion
| Sharpening based on an atomic model
|-  
|-  


| Paper
| Paper
| [[2018Han_Fast]]
| [[2019Ramlaul_Filtering]]
| Automatic alignment using fiducial markers
| Local agreement filtering (denoising)
|-  
|-  


| Paper
| Conference
| [[2019Fernandez_residual]]
| [[2020Mullick_SuperResolution]]
| Alignment of tilt series using residual interpolation
| Superresolution from a map
|-  
|-  


| Paper
| Paper
| [[2019Han_Dual]]
| [[2020Ramirez_LocalDeblur]]
| Automatic alignment using fiducial markers in dual tilt series
| Local deblur (local Wiener filter)
|-  
|-  


| Paper
| Paper
| [[2020Sorzano_automatic]]
| [[2020Terwilliger_density]]
| Automatic alignment considering several geometrical distortions
| Density modification of CryoEM maps
|-  
|-  


|}
| Paper
| [[2020Vilas_Bfactor]]
| Global B-factor correction does not represent macromolecules
|-


=== CTF estimation and restoration ===
| Paper
| [[2021Beckers_Interpretation]]
| Improvements from the raw reconstruction to a structure to model
|-


{|
| Paper
| [[2021Kaur_LocSpiral]]
| LocSpiral, LocBsharpen, LocBfactor
|-


| Paper
| Paper
| [[2003Winkler_CTF]]
| [[2021Fernandez_Adjustment]]
| Focus gradient correction in electron tomography
| Map adjustment for subtraction, consensus and sharpening
|-  
|-  


| Paper
| Paper
| [[2006Fernandez_CTF]]
| [[2021Sanchez_DeepEMhancer]]
| CTF determination and correction in electron tomography
| Deep learning algorithm for volume restoration
|-  
|-  


| Paper
| [[2022Gilles_Wilson]]
| A molecular prior distribution for Bayesian inference based on Wilson statistics
|-


| Paper
| Paper
| [[2009Zanetti_CTF]]
| [[2022Vargas_tubular]]
| CTF determination and correction in electron tomography
| Map enhancement by multiscale tubular filter
|-  
|-  


| Paper
| Paper
| [[2009Xiong_CTF]]
| [[2023He_EMReady]]
| CTF determination and correction for low dose tomographic tilt series
| Map enhancement with local and non-local deep learning (EMReady)
|-  
|-  


| Paper
| Paper
| [[2012Eibauer_CTF]]
| [[2023Maddhuri_EMGan]]
| CTF determination and correction
| Map enhancement with GANs (EMGan)
|-  
|-  


| Paper
| Paper
| [[2015Bharat_CTFCorrectedSubtomogramAveraging]]
| [[2024Agarwal_crefDenoiser]]
| Subtomogram averaging with CTF correction using a Bayesian prior
| cRefDenoiser: map denoising based on deep learning
|-  
|-  


| Paper
| Paper
| [[2017Turonova_3DCTF]]
| [[2024Kimanius_Blush]]
| 3D CTF Correction
| Blush: data-driven regularization
|-  
|-  


| Paper
| Paper
| [[2017Kunz_3DCTF]]
| [[2025Selvaraj_CryoTEN]]
| 3D CTF Correction
| CryoTEN: map enhancement using transformers
|-  
|-  


|}
|}


=== 3D reconstruction ===
=== CTF estimation and restoration ===


{|
{|


| Paper
| Paper
| [[1972Gilbert_SIRT]]
| [[1982Schiske_Correction]]
| Simultaneous Iterative Reconstruction Technique (SIRT)
| CTF correction for tilted objects
|-  
|-  


| Paper
| Paper
| [[1973Herman_ART]]
| [[1988Toyoshima_Model]]
| Algebraic Reconstruction Technique (ART)
| CTF estimation
|-  
|-  


| Paper
| Paper
| [[1984Andersen_SART]]
| [[1995Frank_Wiener]]
| Simultaneous Algebraic Reconstruction Technique (SART)
| CTF correction using Wiener filter
|-  
|-  


| Paper
| Paper
| [[1992Radermacher_WBP]]
| [[1996Skoglund_MaxEnt]]
| Weighted Backprojection in electron tomography
| CTF correction with Maximum Entropy
|-  
|-  


| Paper
| Paper
| [[1997Marabini_reconstruction]]
| [[1996Zhou_Model]]
| Iterative reconstruction in electron tomography
| CTF model and user interface for manual fitting
|-  
|-  


| Paper
| Paper
| [[2002Fernandez_reconstruction]]
| [[1997Fernandez_AR]]
| Iterative reconstruction in electron tomography
| PSD estimation using periodogram averaging and AR models
|-  
|-  


| Paper
| Paper
| [[2007Radermacher_WBP]]
| [[1997Penczek_Wiener]]
| Weighted Backprojection in electron tomography
| CTF correction using Wiener filter
|-  
|-  


| Paper
| Paper
| [[2008Fernandez_CARP]]
| [[1997Stark_Deconvolution]]
| Component Averaged Row Projections (CARP)
| CTF correction using deconvolution
|-  
|-  


| Paper
| Paper
| [[2010Xu_Long]]
| [[1997Zhu_RecCTF]]
| Iterative reconstructions with long object correction and GPU implementation
| CTF correction and reconstruction
|-  
|-  


| Paper
| Paper
| [[2012Herman General Superiorization]]
| [[2000DeRosier_EwaldCorrection]]
| Superiorization: an optimization heuristic for medical physics
| CTF correction considering the Ewald sphere
|-  
|-  


| Paper
| Paper
| [[2012Zhang_IPET_FETR]]
| [[2000Jensen_TiltedCorrection]]
| IPET and FETR, a reconstruction algorithm for single molecule tomography
| CTF correction considering tilt in backprojection
|-  
|-  


| Paper
| Paper
| [[2013Goris_SIRT_TV_DART]]
| [[2001Saad_CTFEstimate]]
| Combination of SIRT, Total Variation and Discrete ART to reconstruct and segment at the same time
| CTF estimation
|-  
|-  


| Paper
| Paper
| [[2013Briegel A_Challenge]]
| [[2003Huang_CTFEstimate]]
| The challenge of determining handedness in electron tomography and the use of DNA origami gold nanoparticle helices as molecular standards
| CTF estimation
|-  
|-  


| Paper
| Paper
| [[2013Messaoudi_EnergyFiltered]]
| [[2003Mindell_CTFTILT]]
| 3D Reconstruction of Energy-Filtered TEM
| CTF estimation for tilted micrographs
|-  
|-  


| Paper
| Paper
| [[2015Venkatakrishnan_MBIR]]
| [[2003Sander_MSA]]
| 3D Reconstruction with priors
| CTF estimation through MSA classification of PSDs
|-  
|-  


| Paper
| Paper
| [[2016Deng_ICON]]
| [[2003Velazquez_ARMA]]
| 3D Reconstruction with missing information restoration
| PSD and CTF estimation using ARMA models
|-  
|-  


| Paper
| Paper
| [[2016Guay_Compressed]]
| [[2004Sorzano_IDR]]
| 3D Reconstruction using compressed sensing
| CTF restoration and reconstruction with Iterative Data Refinement
|-  
|-  


| Paper
| Conference
| [[2016Turonova_Artifacts]]
| [[2004Wan_CTF]]
| Artifacts observed during 3D reconstruction
| Spatially variant CTF
|-  
|-  


| Paper
| Paper
| [[2019Yan_MBIR]]
| [[2004Zubelli_Chahine]]
| 3D Reconstruction with priors and demonstration of its use in biological samples
| CTF restoration and reconstruction with Chahine's multiplicative method
|-  
|-  


| Paper
| Conference
| [[2020Sanchez_Hybrid]]
| [[2005Dubowy_SpaceVariant]]
| 3D reconstruction with a special acquisition and alignment scheme
| CTF correction when this is space variant
|-  
|-  


| Paper
| Paper
| [[2020Song_Tygress]]
| [[2005Mallick_ACE]]
| 3D reconstruction with a special acquisition and alignment scheme
| CTF estimation
|- Hybrid subtomogram averaging - single particle cryo-EM
|-  
 
|}
 
=== Noise reduction ===
{|


| Paper
| Paper
| [[2001Frangakis_NAD]]
| [[2006Wolf_Ewald]]
| Noise reduction with Nonlinear Anisotropic Diffusion
| CTF correction considering Ewald sphere
|-  
|-  


| Paper
| Paper
| [[2003Fernandez_AND]]
| [[2007Jonic_EnhancedPSD]]
| Anisotropic nonlinear diffusion for electron tomography
| PSD enhancement for better identification of Thon rings; Vitreous ice diffracts in Thon rings
|-  
|-  


| Paper
| Paper
| [[2003Jiang_Bilateral]]
| [[2007Philippsen_Model]]
| Bilateral denoising filter in electron microscopy
| CTF Model for tilted specimens
|-  
|-  


| Paper
| Paper
| [[2005Fernandez_AND]]
| [[2007Sorzano_CTF]]
| Anisotropic nonlinear denoising in electron tomography
| CTF estimation using enhanced PSDs
|-  
|-  


| Paper
| Paper
| [[2007Heide_median]]
| [[2009Sorzano_Sensitivity]]
| Iterative median filtering in electron tomography
| Error sensitivity of the CTF models, non-uniqueness of the CTF parameters
|-
|-  


| Paper
| Paper
| [[2007Fernandez_autAND]]
| [[2010Jiang2010_CTFCorrection]]
| Anisotropic nonlinear diffusion with automated parameter tuning
| Amplitude correction method
|-
|-  


| Paper
| Paper
| [[2009Fernandez_Beltrami]]
| [[2010Kasantsev_CTFCorrection]]
| Nonlinear filtering based on Beltrami flow
| Mathematical foundations of Kornberg and Jensen method
|-  
|-  
 
| Paper
| Paper
| [[2010Bilbao_MeanShift]]
| [[2010Leong_CTFCorrection]]
| Mean Shift Filtering
| Correction for spatially variant CTF
|-  
|-  


| Paper
| Paper
| [[2014Kovacik_wedgeArtefacts]]
| [[2011Glaeser_Coma]]
| Removal of wedge artefacts
| The effect of coma at high-resolution
|-  
|-  


| Paper
| Paper
| [[2014Maiorca_beadArtefacts]]
| [[2011Mariani_Tilted]]
| Removal of gold bead artefacts
| CTF simulation and correction of tilted specimens
|-  
|-  


| Paper
| Paper
| [[2018Trampert_Inpainting]]
| [[2011Sindelar_Wiener]]
| Removal of the missing wedge by inpainting
| CTF correction using a modified version of Wiener filter
|-  
|-  


| Paper
| Paper
| [[2018Moreno_TomoEED]]
| [[2011Voortman_Tilted]]
| Fast Anisotropic Diffusion
| CTF correction for tilted specimen
|-  
|-  


| Paper
| Paper
| [[2018Wu_Enhancement]]
| [[2012Voortman_VaryingCTF]]
| Enhancing the image contrast of electron tomography
| Correcting a spatially varying CTF
|-  
|-  


|}
| Paper
 
| [[2013Vargas_FastDef]]
=== Segmentation ===
| Fast defocus
 
|-
{|


| Paper
| Paper
| [[2002Frangakis_Eigenanalysis]]
| [[2014Penczek_CTER]]
| Segmentation using eigenvector analysis.
| Estimation of the CTF errors
|-  
|-  


| Paper
| Paper
| [[2002Volkmann_Watershed]]
| [[2015Rohou_CTFFind4]]
| Segmentation using watershed transform.
| CTF Find 4
|-  
|-  


| Paper
| Paper
| [[2003Bajaj_BoundarySegmentation]]
| [[2015Sheth_CTFquality]]
| Segmentation based on fast marching.
| Visualization and quality assessment of CTF
|-
|-  


| Paper
| Paper
| [[2005Cyrklaff_Thresholding]]
| [[2016Zhang_GCTF]]
| Segmentation using optimal thresholding.
| gCTF
|-  
|-  


| Paper
| Paper
| [[2007Lebbink_TemplateMatching]]
| [[2018Su_GoCTF]]
| Segmentation using template matching.
| goCTF, CTF for tilted specimens
|-  
|-  


| Paper
| Paper
| [[2007Sandberg_OrientationFields]]
| [[2020Heimowitz_Aspire]]
| Segmentation using orientation fields.
| CTF determination in Aspire
|-  
|-  


| Paper
| Paper
| [[2007Sandberg_SegmentationReview]]
| [[2020Zivanov_HighOrder]]
| Review on segmentation in electron tomography.
| Estimation of high-order aberrations
|-  
|-  


| Paper
| Paper
| [[2008Garduno_FuzzySegmentation]]
| [[2022Pant_ExitWave]]
| Segmentation using fuzzy set theory principles.
| Estimation of the electron exit-wave
|-  
|-  


| Paper
| Paper
| [[2009Lebbink_TemplateMatching2]]
| [[2023Fernandez_Local]]
| Segmentation using template matching.
| Local defocus estimation
|-  
|-  


| Paper
| Paper
| [[2012RubbiyaAli_EdgeDetection]]
| [[2025Elferich_CTFFind5]]
| Parameter-Free Segmentation of Macromolecular Structures.
| Quality, tilt, and thickness of TEM samples with CTFFind5
|-  
|-  


| Conference
|}
| [[2015Xu_TemplateMatching]]
 
| Detection of macromolecular complexes with a reduced representation of the templates.
=== Segmentation ===
 
{|
 
| Paper
| [[2006Baker_segmentation]]
| Segmentation of molecular subunits
|-  
|-  


| Paper
| Paper
| [[2017Ali_RAZA]]
| [[2010Pintilie_segger]]
| Automated segmentation of tomograms
| Segmentation of molecular subunits
|-  
|-  


| Paper
| Conference
| [[2017Chen_Annotation]]
| [[2017Nissenson_VolumeCut]]
| Automated annotation of tomograms
| Segmentation of an EM volume using an atomic model
|-  
|-  


| Paper
| Paper
| [[2017Tasel_ActiveContours]]
| [[2019Beckers_FDR]]
| Segmentation with active contours
| Segmentation of the protein using False Discovery Rate
|-  
|-  


| Paper
| Paper
| [[2017Xu_DeepLearning]]
| [[2020Beckers_FDR]]
| Finding proteins in tomograms using deep learning
| Segmentation of the protein using False Discovery Rate (GUI)
|-  
|-  


| Paper
| Paper
| [[2018Zeng_DeepLearning]]
| [[2020Farkas_MemBlob]]
| Mining features in Electron Tomography by deep learning
| Segmentation of membrane in membrane embedded proteins
|-  
|-  


| Paper
| Paper
| [[2020Salfer_PyCurv]]
| [[2020Terashi_MainMastSeg]]
| Curvature analysis of segmented tomograms
| Segmentation of proteins into domains
|-  
|-  
|}
=== Resolution ===
{|


| Paper
| Paper
| [[2005Cardone_Resolution]]
| [[2022Ranno_Neural]]
| Resolution criterion for electron tomography
| Neural representation of a map
|-  
|-  


| Chapter
| Paper
| [[2007Penczek_Resolution]]
| [[2021He_EMNUSS]]
| Review of resolution criteria for electron tomography
| EMNUSS: Identification of secondary structure in CryoEM maps with deep learning
|-  
|-  


| Paper
| Paper
| [[2015Diebolder_ConicalFSC]]
| [[2024Sazzed_CryoSSESeg]]
| Conical Fourier Shell Correlation
| CryoSSESeg: Identification of secondary structure in CryoEM maps with deep learning
|-  
|-  


| Paper
| Paper
| [[2020Vilas_Monotomo]]
| [[2025Cao_EMInfo]]
| Resolution determination in tomograms
| EMInfo: Segmentation of secondary structure and nucleic acids in CryoEM maps
|-
|-  


|}
|}


=== Subtomogram analysis ===
=== Fitting and docking ===


{|
{|


| Paper
| Paper
| [[2000Bohm_Template]]
| [[1999Volkmann_Fitting]]
| Macromolecule finding by template matching
| Fitting in real space
|-  
|-  


| Paper
| Paper
| [[2002Frangakis_Template]]
| [[2001Baker_Review]]
| Macromolecule finding by template matching
| Review of protein structure prediction
|-  
|-  


| Paper
| Paper
| [[2006Nickell_Review]]
| [[2001Jones_Review]]
| Review of macromolecule finding by template matching (Visual Proteomics)
| Review of protein structure prediction
|-  
|-  


| Paper
| Paper
| [[2007Best_Review]]
| [[2003Kovacs_FRM3D]]
| Review of Localization of Protein Complexes by Pattern Recognition
| Fast Rotational Alignment of two EM maps
|-  
|-  


| Paper
| Paper
| [[2007Forster_Review]]
| [[2004Tama_NMA1]]
| Review of structure determination by subtomogram averaging
| Flexible fitting with Normal Modes (I)
|-
|-  


| Paper
| Paper
| [[2008Forster_Classification]]
| [[2004Tama_NMA2]]
| Classification of subtomograms using constrained correlation
| Flexible fitting with Normal Modes (II)
|-
|-  


| Paper
| Paper
| [[2008Bartesaghi_Classification]]
| [[2005Velazquez_Superfamilies]]
| Classification and averaging of subtomograms
| Recognition of the superfamily folding in medium-high resolution volumes
|-
|-  


| Paper
| Paper
| [[2008Schmid_Averaging]]
| [[2007DeVries_Haddock]]
| Alignment and averaging of subtomograms
| Docking with Haddock 2.0
|-
|-  


| Paper
| Paper
| [[2010Amat_Averaging]]
| [[2007Kleywegt_QualityControl]]
| Alignment and averaging of subtomograms exploiting thresholding in Fourier space
| Quality control and validation of fitting
|-
|-  


| Paper
| Paper
| [[2010Yu_PPCA]]
| [[2008Orzechowski_Flexible]]
| Probabilistic PCA for volume classification
| Flexible fitting with biased molecular dynamics
|-
|-  


| Paper
| Paper
| [[2013Chen_Averaging]]
| [[2008Rusu_Interpolation]]
| Fast alignment of subtomograms using spherical harmonics
| Biomolecular pleiomorphism probed by spatial interpolation of coarse models
|-
|-  
 
 
| Paper
| Paper
| [[2013Kuybeda_Averaging]]
| [[2012Biswas_Secondary]]
| Alignment and averaging of subtomograms using the nuclear norm of the cluster
| Secondary structure determination in EM volumes
|-
|-  


| Paper
| Paper
| [[2013Shatsky_Averaging]]
| [[2012Velazquez_Constraints]]
| Alignment and averaging of subtomograms with constrained cross-correlation
| Multicomponent fitting by using constraints from other information sources
|-
|-  


| Paper
| Paper
| [[2013Yu_Projection]]
| [[2013Chapman MS_Atomicmodeling]]
| Subtomogram averaging by aligning their projections
| Atomic modeling of cryo-electron microscopy reconstructions--joint refinement of model and imaging parameters
|-
|-  


| Paper
| Paper
| [[2014Chen_Autofocus]]
| [[2013Esquivel_Modelling]]
| Subtomogram averaging and classification with special attention to differences
| Review on modelling (secondary structure, fitting, ...)
|-
|-  


| Paper
| Paper
| [[2014Yu_ReferenceBias]]
| [[2013Lopez_Imodfit]]
| Scoring the reference bias
| Fitting based on vibrational analysis
|-
|-  


| Paper
| Paper
| [[2014Voortman_LimitingFactors]]
| [[2013Nogales_3DEMLoupe]]
| Limiting factors of subtomogram averaging
| Normal Mode Analysis of reconstructed volumes
|-
|-  


| Paper
| Paper
| [[2015Bharat_CTFCorrectedSubtomogramAveraging]]
| [[2014AlNasr_Secondary]]
| Subtomogram averaging with CTF correction using a Bayesian prior
| Identification of secondary structure elements in EM volumes
|-  
|-  


| Paper
| Paper
| [[2015Yu_ReferenceBias]]
| [[2014Politis_MassSpect]]
| Scoring the reference bias
| Integration of mass spectroscopy information
|-
|-  


| Paper
| Paper
| [[2016Bharat_Relion]]
| [[2014Rey_MassSpect]]
| Subtomogram averaging with Relion
| Integration of mass spectroscopy information
|-
|-  


| Paper
| Paper
| [[2016Song_MatrixNorm]]
| [[2014Villa_Review]]
| Matrix norm minimization for tomographic reconstruction and alignment
| Review of atomic fitting into EM volumes
|-
|-  


| Paper
| Paper
| [[2017Castano_ParticlePicking]]
| [[2015Barad_EMRinger]]
| Particle picking in tomograms for subtomogram averaging
| Validation of hybrid models
|-
|-  


| Paper
| Paper
| [[2017Frazier_Tomominer]]
| [[2015Bettadapura_PF2Fit]]
| TomoMiner a software platform for large-scale subtomogram analysis
| Fast rigid fitting of PDBs into EM maps
|-
|-  


| Paper
| Paper
| [[2018Himes_emClarity]]
| [[2015Carrillo_CapsidMaps]]
| emClarity for subtomogram averaging
| Analysis of virus capsids using Google Maps
|-
|-  


| Paper
| Paper
| [[2018Zhao_Fast]]
| [[2015Hanson_Continuum]]
| Fast alignment and maximum likelihod for subtomogram averaging
| Modelling assemblies with continuum mechanics
|-
|-  


| Paper
| Paper
| [[2019Fokine_Enhancement]]
| [[2015Lopez_Review]]
| Subtomogram enhancement through the locked self-rotation
| Review of structural modelling from EM data
|-
|-  


| Paper
| Paper
| [[2019Han_Constrained]]
| [[2015Schroeder_Hybrid]]
| Constrained reconstruction to enhance resolution
| Review on model building
|-
|-  


| Paper
| Paper
| [[2020Basanta_workflow]]
| [[2015Tamo_Dynamics]]
| Workflow for subtomogram averaging
| Dynamics in integrative modeling
|-
|-  


|}
| Paper
| [[2015Sorzano_AtomsToVoxels]]
| Accurate conversion of an atomic model into a voxel density volume
|-


=== Single particle tomography ===
| 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
| Paper
| [[2012Bartesaghi_Constrained]]
| [[2016Murshudov_Refinement]]
| 3D reconstruction by imposing geometrical constraints
| Refinement of atomic models in high-resolution EM reconstructions
|-
|-  


| Paper
| Paper
| [[2015Galaz_SingleParticleTomography]]
| [[2016Segura_3Diana]]
| Set of tools for Single Particle Tomography in EMAN2
| Validation of hybrid models
|-  
|-  


| Paper
| Paper
| [[2016Galaz_SingleParticleTomography]]
| [[2016Singharoy_MDFF]]
| Alignment algorithms and CTF correction
| Construction of hybrid models driven by EM density and molecular dynamics
|-  
|-  


|}
| Paper
| [[2016Wang_Rosetta]]
| Construction of hybrid models driven by EM density using Rosetta
|-


=== Single-molecule 3D structure ===
| Paper
| [[2017Chen_CoarseGraining]]
| Coarse graining of EM volumes
|-  


{|
| Paper
| [[2017Joseph_Metrics]]
| Metrics analysis for the comparison of structures
|-


| Paper
| Paper
| [[2012Zhang_IPET_FETR]]
| [[2017Hryc_WeightedAtoms]]
| FETR: a focused reconstruction algorithm for a single molecule 3D structure
| Construction of hybrid models by locally weighting the different atoms
|-
|-  


|}
| Paper
| [[2017Matsumoto_Distribution]]
| Estimating the distribution of conformations of atomic models
|-


=== Missing-wedge correction ===
| Paper
| [[2017Michel_ContactPrediction]]
| Structure prediction by contact prediction
|-  


{|
| Paper
| [[2017Miyashita_EnsembleFitting]]
| Ensemble fitting using Molecular Dynamics
|-


| Paper
| Paper
| [[2020Kovacs_Filaments]]
| [[2017Turk_ModelBuilding]]
| Removal of missing wedge artifacts in filamentous tomograms
| Tutorial on model building and protein visualization
|-  
|-  


| Paper
| Paper
| [[2020Moebel_MCMC]]
| [[2017Wang_PartialCharges]]
| Missing wedge correction with Monte Carlo Markov Chains
| Appearance of partial charges in EM maps
|-
|-  


| Paper
| Paper
| [[2020Zhai_LoTTor]]
| [[2017Wlodawer]]
| Missing-wedge correction by LoTTor ('''Lo'''w-'''T'''ilt '''T'''omographic 3D '''R'''econstruction for a single molecule structure)
| Comparison of X-ray and EM high resolution structures
|-
|-  


|}
| Paper
 
| [[2018Cassidy_review]]
=== Molecular 3D dynamics  ===
| Review of methods for hybrid modeling
 
|-
{|


| Paper
| Paper
| [[2015Zhang_IPET]]
| [[2018Chen_SudeChains]]
| 3D structural fluctuation of macromoles)
| A comparison of side chains between X-ray and EM maps
|-
|-  


|}
| Paper
 
| [[2018Kawabata_Pseudoatoms]]
=== Books and reviews ===
| Modelling the EM map with Gaussian pseudoatoms
 
|-
{|


| Paper
| Paper
| [[2000Baumeister_Review]]
| [[2018Kovacs_Medium]]
| Review of electron tomography
| Modelling of medium resolution EM maps
|-  
|-  


| Paper
| Paper
| [[2003Koster_Review]]
| [[2018Neumann_validation]]
| Review of electron tomography
| Validation of fitting, resolution assessment and quality of fit
|-  
|-  


| Paper
| Paper
| [[2003Sali_Review]]
| [[2018Terwilliger_map_to_model]]
| Review of electron tomography
| Phenix map_to_model, automatic modelling of EM volumes
|-  
|-  


| Paper
| Paper
| [[2004Henderson_Review]]
| [[2018Wang_MD]]
| Review of electron microscopy
| Constructing atomic models using molecular dynamics
|-  
|-  


| Paper
| Paper
| [[2005Lucic_Review]]
| [[2018Xia_MVPENM]]
| Review of electron tomography
| Multiscale Normal Mode Analysis
|-  
|-  


| Paper
| Paper
| [[2006Fernandez_Review]]
| [[2018Yu_Atomic]]
| Review of electron microscopy
| Constructing atomic models using existing tools
|-  
|-  


| Book
| Paper
| [[2006Frank_TomoBook]]
| [[2019Bonomi_Multiscale]]
| Electron Tomography
| Bayesian multi-scale modelling
|-  
|-  


| Book
| Paper
| [[2007McIntosh_Book]]
| [[2019Kidmose_Namdinator]]
| Cellular Electron Microscopy
| Namdinator: Flexible fitting with NAMD
|-  
|-  


| Paper
| Paper
| [[2007Sorzano_Review]]
| [[2019Kim_CryoFit]]
| Review of the image processing steps
| CryoFit: flexible fitting in Phoenix
|-  
|-  


| Paper
| Paper
| [[2008Fanelli_ImageFormation]]
| [[2019Klaholz_Review]]
| Review on the image formation model from the electron waves and open inverse-problems
| Review of Phenix tools to modelling
|-  
|-  


| Paper
| Paper
| [[2008Fernandez_HPCReview]]
| [[2019Subramaniya_DeepSSE]]
| High performance computing in electron cryomicroscopy
| Secondary structure prediction from maps using deep learning
|-  
|-  


| Paper
| Paper
| [[2008Jonic_Review]]
| [[2019Zhang_CoarseGrained]]
| Comparison between electron tomography and single particles
| Coarse-graining of EM maps
|-  
|-  


| Paper
| Paper
| [[2012Kudryashev_Review]]
| [[2020Costa_MDeNM]]
| Review of subtomogram averaging
| Flexible fitting with molecular dynamics and normal modes
|-  
|-  


| Paper
| Paper
| [[2013Briggs_Review]]
| [[2020Cragnolini_Tempy2]]
| Review of subtomogram averaging
| TEMpy2 library for density-fitting and validation
|-  
|-  


| Paper
| Paper
| [[2016Beck_Review]]
| [[2020Dodd_ModelBuilding]]
| Review of molecular sociology
| Model building possibilities, with special emphasis on flexible fitting
|-  
|-  


| Paper
| Paper
| [[2016Ercius_Review]]
| [[2020Ho_CryoID]]
| Electron tomography for hard and soft materials research
| Identification of proteins in structural proteomics from cryoEM volumes
|-  
|-  


| Paper
| Paper
| [[2017Galaz_Review]]
| [[2020Hoh_Buccaneer]]
| Review of single particle tomography
| Structure modelling with Buccaneer
|-  
|-  


| Paper
| Paper
| [[2017Plitzko_Review]]
| [[2020Joseph_comparison]]
| Review of electron tomography, FRET and FIB milling
| Comparison of map and model, or two maps
|-  
|-  


| Paper
| Paper
| [[2019Schur_Review]]
| [[2020Kim_Review]]
| Review of electron tomography and subtomogram averaging
| Review of the options for atomic modelling
|-  
|-  
|}
=== Software ===
{|


| Paper
| Paper
| [[1996Kremer_IMOD]]
| [[2020Leelananda_Constraints]]
| IMOD
| NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD structure refinement
|-  
|-  


| Paper
| Paper
| [[1996Chen_Priism/IVE]]
| [[2020Liebschner_Ceres]]
| Priism/IVE
| CERES: Web server of refined atomic maps of CryoEM deposited maps by Phenix
|-  
|-  


| Paper
| Paper
| [[1996Frank_Spider]]
| [[2020Oroguchi]]
| Spider
| Assessment of Force Field Accuracy Using Cryogenic Electron Microscopy Data
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2020Vant_Flexible]]
| Xmipp
| Flexible fitting with molecular dynamics and neural network potentials
|-  
|-  


| Paper
| Paper
| [[2005Nickell_TOM]]
| [[2021Behkamal_Secondary]]
| TOM Toolbox
| Secondary structure from medium resolution maps
|-  
|-  


| Paper
| Paper
| [[2007Messaoudi_TomoJ]]
| [[2021Chojnowski_quality]]
| TomoJ
| Quality of models automatically fitted with ARP/wARP
|-  
|-  


| Paper
| Paper
| [[2008Heymann_BsoftTomo]]
| [[2021Han_Vesper]]
| Bsoft
| VESPER: global and local cryo-EM map alignment using local density vectors
|-  
|-  


| Paper
| Paper
| [[2012Zhang IPET FETR]]
| [[2021Lawson_Challenge]]
| IPET
| Validation recommendations based on outcomes of the 2019 EMDataResource challenge
|-  
|-  


| Paper
| Paper
| [[2015Ding_CaltechTomography]]
| [[2021Mori_Flexible]]
| Caltech tomography database
| Efficient Flexible Fitting Refinement with Automatic Error Fixing
|-  
|-  


| Paper
| Paper
| [[2015Noble_AppionProtomo]]
| [[2021Pfab_DeepTracer]]
| Batch fiducial-less tilt-series alignment in Appion using Protomo
| DeepTracer for fast de novo cryo-EM protein structure modeling
|-  
|-  


| Paper
| Paper
| [[2015vanAarle_Astra]]
| [[2021Saltzberg_IMP]]
| ASTRA Toolbox
| Using the Integrative Modeling Platform to model a cryoEM map
|-  
|-  


| Paper
| Paper
| [[2016Liu_FullMechTomo]]
| [[2021Terwilliger_CryoID]]
| Fully mechanically controlled automated electron microscopic tomography
| Identification of sequence in a CryoEM map from a set of candidates
|-  
|-  


| Paper
| Paper
| [[2017Han_AuTom]]
| [[2021Titarenko_LocalCorr]]
| Software platform for Electron Tomography
| 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
| Paper
| [[2017Wan_Simulator]]
| [[2022Antanasijevic_ab]]
| Electron Tomography Simulator
| Sequence determination of antibodies bound to a map
|-  
|-  
|}
== 2D Crystals ==
=== 2D Preprocessing ===
{|


| Paper
| Paper
| [[1982Saxton_Averaging]]
| [[2022Behkamal_LPTD]]
| Radial Correlation Function
| LPTD: Topology determination of CryoEM maps
|-  
|-  


| Paper
| Paper
| [[1984Saxton_Distortions]]
| [[2022Bouvier_coevolution]]
| 3D Reconstruction of distorted crystals
| Atomic modelling exploiting residue coevolution
|-  
|-  


| Paper
| Paper
| [[1986Henderson_Processing]]
| [[2022Chojnowski_findMySeq]]
| General 2D processing
| Identify sequence in CryoEM map using Deep Learning
|-  
|-  


| Paper
| Paper
| [[2000He_PhaseAlignment]]
| [[2022Hryc_Pathwalking]]
| Phase consistency and Alignment
| Atomic modelling with Pathwalking
|-  
|-  


| Paper
| Paper
| [[2006Gil_Unbending]]
| [[2022He_EMBuild]]
| Crystal unbending
| Atomic modelling for complexes with EMbuild
|-  
|-  


|}
| Paper
 
| [[2022Krieger_Prody2]]
=== Classification ===
| Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0
{|
|-


| Paper
| Paper
| [[1988Frank_Classification]]
| [[2022Neijenhuis_Haddock]]
| MSA and classification in electron crystallography
| Protein-protein interface refinement in complex maps with Haddock2.4
|-  
|-  


| Paper
| Paper
| [[1996Fernandez_SOM]]
| [[2022Terwilliger_AlphaFold]]
| Classification based on self organizing maps
| Iterative modelling with AlphaFold and experimental maps
|-  
|-  


| Paper
| Paper
| [[1998Sherman_MSA]]
| [[2022Urzhumtsev_Direct]]
| Classification based on MSA
| Calculation of the EM map from an atomic model
|-  
|-  
|}
=== 3D Reconstruction ===
{|


| Paper
| Paper
| [[1985Wang_Solvent]]
| [[2022Urzhumtsev_XrayEM]]
| Solvent flattening
| Effect of the local resolution on the atomic modeling
|-  
|-  


| Paper
| Paper
| [[1990Henderson_Processing]]
| [[2022Vuillemot_NMMD]]
| General 3D processing
| NMMD: Flexible fitting with simultaneous Normal Mode and Molecular Dynamics displacements
|-
|-  


| Paper
| Paper
| [[2004Marabini_ART]]
| [[2022Zhang_CRITASSER]]
| Algebraic Reconstruction Technique with blobs for crystals (Xmipp)
| Atomic models of assemble protein structures with deep learning
|-  
|-  


| Paper
| Paper
| [[2018Biyani_Badlu]]
| [[2023Blau_FittingML]]
| Image processing for badly ordered crystals
| Maximum-likelihood fitting of atomic models in EM maps
|-  
|-  
|}
=== Books and reviews ===
{|


| Paper
| Paper
| [[1998Walz_Review]]
| [[2023Chang_CryoFold]]
| Review of 2D crystallography
| Flexible fitting into cryo-EM maps with CryoFold (a MELD plugin)
|-  
|-  


| Paper
| Paper
| [[1999Glaeser_Review]]
| [[2023Dai_CryoFEM]]
| Review of 2D crystallography
| CryoFEM: Deep learning+AlphaFold 2 for the interpretation of maps
|-  
|-  


| Paper
| Paper
| [[2001Ellis_Review]]
| [[2023Millan_LL]]
| Review of 2D crystallography
| Likelihood-based docking of models into cryo-EM maps
|-  
|-  


| Paper
| Paper
| [[2001Glaeser_Review]]
| [[2023Park_CSA]]
| Review of 2D crystallography
| Atomic model fitting using conformational space annealing
|-  
|-  


| Paper
| Paper
| [[2004Henderson_Review]]
| [[2023Read_LL]]
| Review of electron microscopy
| Likelihood-based signal and noise analysis for docking of models into cryo-EM maps
|-  
|-  


| Paper
| Paper
| [[2006Fernandez_Review]]
| [[2023Reggiano_MEDIC]]
| Review of single particles, electron tomography and crystallography
| Evaluation of atomic models using MEDIC
|-  
|-  


| Paper
| Paper
| [[2007Sorzano_Review]]
| [[2023Richardson_Overfitting]]
| Review of the image processing steps
| Evaluation of overfitting errors in model building
|-  
|-  


|}
| Paper
| [[2023Sweeney_ChemEM]]
| ChemEM: Flexible Docking of Small Molecules in Cryo-EM Structures
|-


=== Software ===
| Paper
| [[2023Terashi_DAQrefine]]
| Atomic model refinement using AlphaFold2 and DAQ
|-


{|
| Paper
| [[2023Terashi_DeepMainMast]]
| DeepMainMast: de novo modelling of CryoEM maps
|-


| Paper
| Paper
| [[1996Crowther_MRC]]
| [[2023Terwilliger_AlphaFold]]
| MRC
| Comparison of AlphaFold predictions with experimental maps and models
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2023Wang_CryoREAD]]
| Xmipp
| CryoREAD: de novo modelling of nucleic acids
|-  
|-  


| Paper
| Paper
| [[2007Gipson_2dx]]
| [[2024Beton_Ensemble]]
| 2dx
| Ensemble fitting
|-  
|-  


| Paper
| Paper
| [[2007Heymann_Bsoft]]
| [[2024Chen_EModelX]]
| Bsoft
| Atomic modelling de novo from cryoEM maps
|-  
|-  


| Paper
| Paper
| [[2007Philippsen_IPLT]]
| [[2024Dahmani_MDFF]]
| IPLT
| Accelerated MDFF flexible fitting
|-  
|-  


|}
| Paper
| [[2024Giri_CryoStruct]]
| CryoStruct: de novo modeling of cryoEM maps
|-


== 3D Crystals - MicroED ==
| Paper
| [[2024Gucwa_CMM]]
| CheckMyMetal: Metal analysis in CryoEM maps
|-  


=== Sample Preparation ===
{|
| Paper
| Paper
| [[2016Shi_Preparation]]
| [[2024Jamali_Modelangelo]]
| Sample Preparation
| ModelAngelo: Automated model building of cryoEM maps
|}
|-
=== Data Collection ===
 
{|
| Paper
| Paper
| [[2014Nannenga_CR]]  
| [[2024He_SHOT]]
| Continuous rotation
| Accurate global and local 3D alignment of cryo-EM density maps using local spatial structural features
|-


|}
| Paper
=== Data Processing ===
| [[2024Hoff_EMMIVox]]
{|
| EMMIVox: Model fitting using ensembles and molecular dynamics
|-


| Paper
| Paper
| [[2011Wisedchaisri_PhaseExtension]]
| [[2024Li_EMRNA]]
| Fragment-based phase extension
| EMRNA: de novo modeling of RNA structures
|-
|-  


| Paper
| Paper
| [[2015Hattne_Processing]]  
| [[2024Li_EM2NA]]
| Data Processing
| EM2NA: Detection and de novo modelling of nucleic acids in cryoEM maps
|-
|-  
 
| Paper
| Paper
| [[2016Hattne_Correction]]
| [[2024Read_Interactive]]
| Image correction
| Interactive local docking
|}
|-


=== Software ===
| Paper
{|
| [[2024Wang_DiffModeller]]
| CryoEM map modelling integrating AlphaFold2 and diffusion networks
|-


| Paper
| Paper
| [[2014Iadanza_Processing]]
| [[2024Wankowicz_qFit]]
| Data Processing of still diffraction data
| Multiconformer modeling of cryoEM maps
|}
|-


=== Books and Reviews ===
| Paper
{|
| [[2024Wlodarski_cryoEnsemble]]
| Paper
| CryoEnsemble: cryoEM map interpretation with molecular dynamics simulated ensembles
| [[2014Nannenga_Review ]]
|-  
| Review of MicroED
|-


| Paper
| Paper
| [[2016Liu_Review ]]
| [[2025Carr_Map2Seq]]
| Review of MicroED
| Map-to-sequence workflow
|-
|-  


| Paper
| Paper
| [[2016Rodriguez_Review ]]
| [[2025Chen_GMMs]]
| Review of MicroED
| Model building in heterogeneous maps
|-  
|-  


|}
| Paper
| [[2025Haloi_Ligand]]
| Ligand detection in CryoEM maps using structure prediction and flexible fitting
|-


== Helical particles ==
| Paper
 
| [[2025Karolczak_Ligand]]
=== Filament corrections ===
| Ligand detection in CryoEM maps using deep learning
 
|-
{|


| Paper
| Paper
| [[1986Egelman_Curved]]
| [[2025Luo_DiffFit]]
| Algorithm for correcting curved filaments
| DiffFit: Flexible fitting of map and atomic model
|-  
|-  


| Paper
| Paper
| [[1988Bluemke_Pitch]]
| [[2025Mallet_crAI]]
| Algorithm for correcting filaments with different helical pitches
| crAI: detection of antibodies in cryoEM maps
|-  
|-  


| Paper
| Paper
| [[2006Wang_Pitch]]
| [[2025Matsuoka_ForceConstant]]
| Algorithm for correcting filaments with different helical pitches
| Empirical determination of the force constant for flexible fitting
|-  
|-  


| Paper
| Paper
| [[2016Yang_Flexible]]
| [[2025Muenks_EmeraldID]]
| Algorithm for correcting filaments with flexible subunits
| Emerald ID: Identification of small ligands in cryoEM maps
|-  
|-  


| Paper
| Paper
| [[2019Ohashi_SoftBody]]
| [[2025Riahi_EMPOT]]
| Algorithm for correcting filaments with flexible helices
| EMPOT: aligning partially overlapping maps using Unbalanced Gromov-Wasserstein Divergence
|-  
|-  


|}
| Paper
 
| [[2025Shub_Mic]]
=== Reconstruction ===
| Mic: a deep learning algorithm to assign ions and waters in SPA maps
 
|-
{|


| Paper
| Paper
| [[1952Cochran_Fourier]]
| [[2025Su_CryoAtom]]
| Fourier Bessel transform of filamentous structures
| CryoAtom: Model building using deep learning
|-  
|-  


| Paper
| Paper
| [[1958Klug_Fourier]]
| [[2025Wang_E3CryoFold]]
| Fourier Bessel decomposition of the projection images
| E3CryoFold: model building in cryoEM maps
|-  
|-  


| Paper
| Paper
| [[1970DeRosier_Rec]]
| [[2025Zhang_Emol]]
| Image processing steps towards 3D reconstruction
| Emol: modeling protein-nucleic acid complex structures from cryo-EM maps
|-  
|-  


| Paper
| Paper
| [[1988Stewart_Rec]]
| [[2025Zhang_Benchmark]]
| Image processing steps towards 3D reconstruction
| Benchmarking multiple algorithms to compute an atomic model from a cryoEM map
|-  
|-  


| Paper
| Paper
| [[1992Morgan_Rec]]
| [[2025Zheng_Disorder]]
| Image processing steps towards 3D reconstruction
| Exploration of disordered regions in CryoEM maps
|-  
|-  


| Paper
|}
| [[2005Wang_Iterative]]
 
| Iterative Fourier-Bessel algorithm
=== Books and reviews ===
 
{|
 
| Book
| [[1980Herman_Tomography]]
| General book on tomography
|-  
|-  


| Paper
| Book
| [[2007Egelman_Iterative]]
| [[1988Kak_Tomography]]
| Iterative real-space algorithm
| General book on tomography
|-  
|-  


| Paper
| Paper
| [[2010Egelman_Pitfalls]]
| [[2000Tao_Review]]
| Pitfalls in helical reconstruction
| Review of single particles
|-  
|-  


| Paper
| Paper
| [[2013Desfosses_Spring]]
| [[2000VanHeel_Review]]
| Helical processing with Spring
| Review of single particles
|-  
|-  


| Paper
| Paper
| [[2015Zhang_seam]]
| [[2002Frank_Review]]
| Workflow for the detection of the lattice seam
| Review of single particles
|-  
|-  


| Paper
| Paper
| [[2016Rohou_Frealix]]
| [[2002Schmid_Review]]
| Helical processing with Frealix
| Review of single particles
|-  
|-  


| Paper
| Paper
| [[2017_He]]
| [[2004Henderson_Review]]
| Helical processing with Relion
| Review of electron microscopy
|-  
|-  


| Paper
| Paper
| [[2019_Pothula]]
| [[2004Subramaniam_Review]]
| 3D Classification through 2D analysis
| Review of single particles
|-  
|-  


|}
| Paper
| [[2005Steven_Review]]
| Review of electron microscopy
|-


=== Validation ===
| Paper
| [[2006Fernandez_Review]]
| Review of electron microscopy
|-


{|
| Book
| [[2006Frank_book]]
| Book covering all aspects of electron microscopy of single particles
|-


| Paper
| Paper
| [[2014Egelman_ambiguity]]
| [[2006Sorzano_Review]]
| How to detect incorrect models
| Review of optimization problems in electron microscopy
|-  
|-  
|}
=== Books and reviews ===
{|


| Paper
| Paper
| [[1970DeRosier_Rec]]
| [[2007Leschziner_Review]]
| Image processing steps towards 3D reconstruction
| Review of 3D heterogeneity handling algorithms
|-  
|-  


| Paper
| Paper
| [[1992Morgan_Rec]]
| [[2007Sorzano_Review]]
| Image processing steps towards 3D reconstruction
| Review of the image processing steps
|-  
|-  


| Paper
| Paper
| [[2004Henderson_Review]]
| [[2008Fanelli_ImageFormation]]
| Review of electron microscopy
| Review on the image formation model from the electron waves and open inverse-problems in Electron Tomography
|-  
|-  


| Paper
| Paper
| [[2015Sachse_Review]]
| [[2008Fernandez_HPCReview]]
| Review of the image processing steps in helical particles
| High performance computing in electron cryomicroscopy
|-  
|-  


|}
| Paper
 
| [[2008Jonic_Review]]
=== Software ===
| Comparison between electron tomography and single particles
 
|-
{|


| Paper
| Paper
| [[1996Carragher_Phoelix]]
| [[2008Mueller_Review]]
| Phoelix
| Review of Electron microscopy
|-  
|-  


| Paper
| Paper
| [[1996Crowther_MRC]]
| [[2008Taylor_Review]]
| MRC
| Review of Electron microscopy
|-  
|-  


| Paper
| Paper
| [[1996Owen_Brandeis]]
| [[2010DeRosier_Review]]
| Brandeis
| Personal account of how 3DEM developed in the early days
|-  
|-  


|}
| Chapter
| [[2012Sorzano_Review]]
| Review of single particle analysis using Xmipp
|-


== Icosahedral particles ==
| Chapter
 
| [[2012Devaux_Protocol]]
=== Reconstruction ===
| Protocols for performing single particle analysis
 
|-
{|


| Paper
| Paper
| [[1970Crowther_Rec]]
| [[2014Bai_Review]]
| Reconstruction of icosahedral viruses in Fourier space
| Recent advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[1971Crowther_Rec]]
| [[2015Carazo_Review]]
| Reconstruction of icosahedral viruses in Fourier space
| Review of the reconstruction process
|-  
|-  


| Paper
| Paper
| [[1996Fuller_Rec]]
| [[2015Cheng_Review]]
| Reconstruction of icosahedral viruses in Fourier space
| A primer to Single Particle Cryo-EM
|-  
|-  


| Paper
| Paper
| [[1997Thuman_Rec]]
| [[2015Cheng_Reviewb]]
| Reconstruction of icosahedral viruses in Fourier space
| Single Particle Cryo-EM at crystallographic resolution
|-  
|-  


| Paper
| Paper
| [[2019Goetschius_Asymmetric]]
| [[2015Elmlund_Review]]
| Approaches to reconstruct asymmetric features in viruses
| Recent advances in cryo-EM
|-  
|-  


|}
| Paper
 
| [[2015Henderson_Review]]
=== Classification ===
| Recent advances in cryo-EM
 
|-
{|


| Paper
| Paper
| [[2005Scheres_Virus]]
| [[2015Nogales_Review]]
| Classification of virus capsids in real space
| Recent advances in cryo-EM
|-  
|-  
|}
=== Books and reviews ===
{|


| Paper
| Paper
| [[1999Baker_Review]]
| [[2015Schroeder_Review]]
| Review of reconstruction of icosahedral viruses
| Review of advances in the electron microscope
|-  
|-  


| Paper
| Paper
| [[1999Conway_Review]]
| [[2015VanDenBedem_Integrative]]
| Review of reconstruction of icosahedral viruses
| Review of integrative structural biology
|-  
|-  


| Paper
| Paper
| [[2000Thuman_Review]]
| [[2015Wu_Review]]
| Review of reconstruction of icosahedral viruses
| Review of advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[2003Lee_Review]]
| [[2016Carroni_CryoEM]]
| Review of reconstruction of icosahedral viruses
| Review of advances in Cryo-EM
|-  
|-  


| Paper
| Paper
| [[2003Navaza_Review]]
| [[2016Egelman_CryoEM]]
| Review of reconstruction of icosahedral viruses
| Review of advances in Cryo-EM
|-  
|-  


| Paper
| Paper
| [[2006Grunewald_Review]]
| [[2016Eisenstein_CryoEM]]
| Review of reconstruction of icosahedral viruses
| News feature on the Method of the Year
|-  
|-  


|}
| Paper
 
| [[2016FernandezLeiro_Review]]
=== Software ===
| Review of EM
 
|-
{|


| Paper
| Paper
| [[1996Baker_EMPFT]]
| [[2016Glaeser_HowGood]]
| EMPFT
| How good can cryo-EM become?
|-  
|-  


| Paper
| Paper
| [[1996Crowther_MRC]]
| [[2016Jonic_PseudoAtoms]]
| MRC
| Review of the applications of the use of pseudoatoms in EM
|-  
|-  


| Paper
| Chapter
| [[1996Frank_Spider]]
| [[2016Mio_Review]]
| Spider
| Overview of the process to obtain EM reconstructions
|-  
|-  


| Paper
| Paper
| [[1996VanHeel_Imagic]]
| [[2016Jonic_Review]]
| Imagic
| A review of computational ways to handle heterogeneity
|-  
|-  


| Paper
| Paper
| [[2004Sorzano_Xmipp]]
| [[2016Nogales_Review]]
| Xmipp
| Review of advances in cryo-EM
|-  
|-  


| Paper
| Paper
| [[2013DeLaRosa_Xmipp30]]
| [[2016Subramaniam_Review]]
| Xmipp 3.0
| Why cryo-EM is now suitable for crystallographic journals
|-  
|-  


| Paper
| Paper
| [[2013Morin_Sliz SBGrid]]
| [[2016Vinothkumar_Review]]
| SBGrid presentation for eLife
| Historical review and current limitations
|-  
|-  


|}
| Report
 
| [[2017Brezinski_Nobel]]
== Liquid-cell TEM / in-situ TEM ==
| 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
| [[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
|-
 
|}
 
== Electron tomography ==
 
=== 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
|-
 
|}
 
=== 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
|-
 
|}
 
=== 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
|-
 
|}
 
=== 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
|-
 
|}
 
=== 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
| Paper
| [[2020Ren_LTEM]]
| [[2018wwwPDB_PDB]]
| Real-time dynamic imaging of sample in liquid phase
| Review of PDB advances
|-  
|-  
|}
== Databases ==
{|


| Paper
| Paper
| [[2003Boutselakis_EMSD]]
| [[2021Nair_PDBe]]
| EMSD database
| PDBe API
|-  
|-  


| Paper
| Paper
| [[2005Heymann_Conventions]]
| [[2022Wang_EMDB]]
| Conventions for software interoperability
| Validation analysis of EMDB entries
|-  
|-  


| Paper
| Paper
| [[2005Heymann_Conventions]]
| [[2022Westbrook_mmCIF]]
| Conventions for software interoperability
| PDBx/mmCIF ecosystem
|-  
|-  


| Paper
| Paper
| [[2011Kim_CDDB]]
| [[2024Kleywegt_ArchivingValidation]]
| Conformational Dynamics Data Bank
| Community recommendations for archival and validation
|-  
|-  


| Paper
| Paper
| [[2011Lawson_EMDB]]
| [[2024Ermel_DataPortal]]
| Electron Microscopy Data Bank
| CryoET Data Portal
|-  
|-  


| Paper
| Paper
| [[2013Ison_EDAM]]
| [[2024Vallat_IHMCIF]]
| EDAM, an ontology of bioinformatics operations
| IHMCIF extension of mmCIF for integrative modelling
|-  
|-  


| Paper
| Paper
| [[2016Iudin_EMPIAR]]
| [[2024wwPDB_EMDB]]
| EMPIAR raw data database
| Review of EMDB
|-
 
| 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
|-  
|-  


Line 5,093: Line 7,909:
| [[2019Jimenez_SAXS]]
| [[2019Jimenez_SAXS]]
| Selection of EM initial volumes by SAXS curves
| 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
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Latest revision as of 15:22, 16 December 2025

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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

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

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_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 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

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 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

Electron tomography

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

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

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

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

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