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Electron microscopy images
Useful resources
Map of cryoEM microscopes and labs in the world
Online courses and Learning material
Caltech (same course in Coursera) (latest version of the course in EM-learning)
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
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
NCCAT Single Particle Analysis short course
Algorithms for Structural Bioinformatics, AlgoSB2023, Cargese
One world CryoEM technical talks
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 | 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 | 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 | 2024Bochtler_Probes | X-rays, electrons, and neutrons as probes of atomic matter |
Paper | 2024Dickerson_magnification | Accurate determination of magnification using gold |
Paper | 2024Parkhurst_IceSimulation | Projections of amorphous ice simulation simulated with Gaussian Random Fields |
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 | 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 | 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 | 2024Henderikx_Vitrojet | Use cases of Vitrojet |
Paper | 2024Liu_Graphene | Review of the use of graphene for grid preparation |
Paper | 2024Mueller_Facility | Sample workflow at the facility |
Paper | 2024Yadav_Orientation | Experimental factors affecting orientation distribution |
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 | 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 |
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 | 2024Fang_Swin | SwinCryoEM: particle picking |
Paper | 2024Huang_Joint | Joint denoising and picking |
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 |
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 |
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 |
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 |
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 |
Paper | 2023Ling_Synch | Synchronization of projection directions |
Paper | 2023Rangan_Fast | Fast angular assignment using Fourier-Bessel |
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 | 2024Titarenko_optimal | Optimal 3D angular sampling |
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 | 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 |
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 | 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 | 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 |
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 |
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 | 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 |
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 |
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 |
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 |
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 |
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 | 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 | 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 | 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 | 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 | 2024Read_Interactive | Interactive local docking |
Paper | 2024Wankowicz_qFit | Multiconformer modeling of cryoEM maps |
Paper | 2024Wlodarski_cryoEnsemble | CryoEnsemble: cryoEM map interpretation with molecular dynamics simulated ensembles |
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 | 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 |
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 | 2024Gonzalez_Dashboard | A web-based dashboard for Relion |
Paper | 2024Herre_Capsules | SBGrid Capsules to execute programs in controlled environments |
Paper | 2024Urzhumtseva_VUE | VUE: Visualization of angular distributions |
Paper | 2024Vuillemot_MDSPACE | MDSpace and MDTomo to analyze continuous heterogeneity |
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 |
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 |
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 |
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 |
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. |
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 | 2024Siggel_ColabSeg | Interactive membrane segmentation of tomograms |
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 | 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 | 2024Cruz_Template | Template matching for cryoET |
Paper | 2024Huang_MiLoPYP | Self-supervised particle localization in tomograms |
Paper | 2024Jin_Size | Subtomogram picking based on size |
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 |
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 |
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 |
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 | 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 | 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 |
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 |
Validation
Paper | 2014Egelman_ambiguity | How to detect incorrect models |
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 |
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 |
Liquid-cell TEM / in-situ TEM
Paper | 2020Ren_LTEM | Real-time dynamic imaging of sample in liquid phase |
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 | 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