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https://github.com/kuixu/awesome-cryoem

A collaborative list of awesome CryoEM (Cryo Electron Microscopy) resources.
https://github.com/kuixu/awesome-cryoem

List: awesome-cryoem

3d-denoise 3d-reconstruction cryo-em cryoem density-map electron-microscopy model-building protein-structures tomography

Last synced: 5 days ago
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A collaborative list of awesome CryoEM (Cryo Electron Microscopy) resources.

Awesome Lists containing this project

README 

        
# Awesome CryoEM

A collaborative list of awesome CryoEM (Electron Cryo-Microscopy) resources. Feel free to contribute!

[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)



Cryo-EM



### Contributing



Please take a quick look at the [contribution guidelines](.github/CONTRIBUTING.md) first. If you see a package or project here that is no longer maintained or is not a good fit, please submit a pull request to improve this file. Thank you to all [contributors](https://github.com/barrykui/awesome-cryoem/graphs/contributors); you rock!



### Contents



- [Guides](#guides)

    - [Official Guides](#official-guides)

    - [Third party Guides](#third-party-guides)

- [Softwares](#softwares) 

- [Technologies](#technologies)

- [Computational Problems](#computational-problems)

- [Validation Metrics](#validation-metrics)

- [DataBases](#database)

- [Active Groups](#active-groups)



## Guides

*An awesome list of CryoEM related guides.* 



### Official Guides

[back to top](#readme) 



* [3 Mins Introduction of CryoEM](https://www.youtube.com/watch?v=BJKkC0W-6Qk) - 3 Mins Introduction of CryoEM for beginners.

* [Single-particle cryo-electron microscopy](http://www.nature.com/nmeth/journal/v13/n1/full/nmeth.3700.html) - Nature Method Review.

* [CryoEM Course](https://www.coursera.org/learn/cryo-em)

* [CryoEM 101](https://cryoem101.org)

* [MRC lab CryoEM](https://www2.mrc-lmb.cam.ac.uk/research/scientific-training/electron-microscopy/)



### Third party Guides

[back to top](#readme) 



* [EMAN2 Video Tutorials](http://blake.bcm.edu/emanwiki/EMAN2/VideoTutorials)



## Methods and Softwares

[back to top](#readme) 



* [UCSF Chimera](https://www.cgl.ucsf.edu/chimera/) - An interactive visualization and analysis of structures.

* [UCSF ChimeraX](https://www.cgl.ucsf.edu/chimera/) - An interactive visualization and analysis of structures. [[code]](https://github.com/RBVI/ChimeraX)

* [Relion](http://www2.mrc-lmb.cam.ac.uk/relion/index.php/Main_Page) - A Bayesian approach to refinement of 3D reconstructions or 2D class averages.

    * [`New` 2.1 ](ftp://ftp.mrc-lmb.cam.ac.uk/pub/scheres/relion21_tutorial.pdf) - Tutorial (v2.1) (The quickest way to learning RELION) 

    * [Nature Protocol Paper](http://www.nature.com/nprot/journal/v11/n11/full/nprot.2016.124.html) - Resolving macromolecular structures from electron cryo-tomography data using subtomogram averaging in RELION



* [COOT](http://www2.mrc-lmb.cam.ac.uk/personal/pemsley/coot/) - A interactive visualization model building, model completion and validation.

* [EMAN2](http://blake.bcm.edu/emanwiki/EMAN2) - A scientific image processing software suite with a focus on CryoEM and CryoET.

* [PHENIX](https://www.phenix-online.org/) - Automated determination of molecular structures using X-ray crystallography and other methods.

* [Rosetta](https://www.rosettacommons.org/) - A software suite includes algorithms for computational modeling and analysis of protein structures.

* [FREALIGN: high-resolution refinement of single particle structures](#)

* [SIMPLE: Software for ab initio reconstruction of heterogeneous single-particles](#)

* [PRIME: probabilistic initial 3D model generation for single-particle cryo-electron microscopy](#)

* [SPIDER](http://spider.wadsworth.org) - System for Processing Image Data from Electron microscopy and Related fields.

* [CCP4](http://www.ccp4.ac.uk/) - Collaborative Computational Project No. 4 Software for Macromolecular X-Ray Crystallography.

    * [Buccaneer](#)

    * [SFTOOLS](#)

* [ResMap](http://resmap.sourceforge.net/) - computing the local resolution of 3D density maps.

* [DeepPicker](https://arxiv.org/abs/1605.01838) - Fully Automated Particle Picking using deep learning.

* [FindEM](http://www.ccpem.ac.uk/ccpem_projects.php) - CCP-EM projects, automated particle picking from electron micrographs, using Fortran

* [EMfold](http://www.meilerlab.org/index.php/servers/show?s_id=18) - Meiler Lab,  placement of helices is restricted to CryoEM density regions.

* [De novo protein structure determination from near-atomic-resolution cryo-EM maps](http://www.nature.com/doifinder/10.1038/nmeth.3287)

* [Atomic accuracy models from 4.5 Å cryo-electron microscopy data with density-guided iterative local refinement](http://www.nature.com/doifinder/10.1038/nmeth.3286)

* [cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination](http://www.nature.com/nmeth/journal/v14/n3/full/nmeth.4169.html)

    * [Building proteins in a day: Efficient 3D molecular reconstruction(CVPR2015)](#)

* [Pathwalker](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3307788/pdf/nihms350767.pdf) - Constructing and Validating Initial Cα Models from Subnanometer Resolution Density Maps with Pathwalking, TSP

* [EMBuilder](https://www.nature.com/articles/s41598-017-02725-w) - EMBuilder: A Template Matching-based Automatic Model-building Program for High-resolution Cryo-Electron Microscopy Maps

* Cryoem-cloud-tools: A software platform to deploy and manage cryo-EM jobs in the cloud. [[paper]](https://europepmc.org/article/PMC/6091888), [[papge]](http://cryoem-tools.cloud/)



## Technologies

[back to top](#readme) 



* [Single Particle](#)

* [Tomography](#)

* [MircoED](#)



## Computational Problems

[back to top](#readme) 



### Particle Picking

* Fully Automatic

    * [DeepPicker](https://arxiv.org/abs/1605.01838) - Fully Automated Particle Picking using deep learning.

    * [FindEM](http://www.ccpem.ac.uk/ccpem_projects.php) - CCP-EM projects, automated particle picking from electron micrographs, using Fortran

    * [DeepEM](http://arxiv.org/pdf/1605.05543v1.pdf) - A deep learning approach to single-particle recognition in cryo-electron microscopy,Yanan Zhu, Qi Ouyang, Youdong Mao.

    * [SPHIRE-crYOLO](https://www.biorxiv.org/content/early/2018/06/26/356584) - SPHIRE-crYOLO: A fast and well-centering automated particle picker for cryo-EM.

    * [PIXER](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2614-y) - PIXER: an automated particle-selection method based on segmentation using a deep neural network.

    * [A fast method for particle picking in cryo-electron micrographs based on fast R-CNN](https://aip.scitation.org/doi/pdf/10.1063/1.4982020)

    * [Real-time cryo-EM data pre-processing with warp](https://www.biorxiv.org/content/10.1101/338558v1)

    * [Topaz](https://arxiv.org/pdf/1803.08207) - Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs, [Nature Method Version](https://www.ncbi.nlm.nih.gov/pubmed/29707703)

    * [DRPnet](https://www.biorxiv.org/content/biorxiv/early/2019/05/05/616169.full.pdf) - Automated Particle Picking in Cryo-Electron Micrographs using Deep Regression. 

    * [AutoCryoPicker](https://www.biorxiv.org/content/10.1101/561928v1) - AutoCryoPicker: An Unsupervised Learning Approach for Fully Automated Single Particle Picking in Cryo-EM Images

    * [DeepCryoPicker](https://www.biorxiv.org/content/10.1101/763839v1.full.pdf) - DeepCryoPicker: Fully Automated Deep Neural Network for Single Protein Particle Picking in cryo-EM

    

* Semi Automatic

    * [AutoPicker](https://www.sciencedirect.com/science/article/pii/S1047847714002615) - Semi-automated selection of cryo-EM particles in RELION-1.3.



### Pre-processing and Denoising 

* **GAN-Denosing** - Generative adversarial networks as a tool to recover structural information from cryo-electron microscopy data. [[paper]](https://www.biorxiv.org/content/early/2018/02/12/256792).

* **Warp** - Real-time cryo-EM data pre-processing with Warp. [[paper]](https://www.biorxiv.org/content/10.1101/338558v1).

* **Topaz-Denoise**: general deep denoising models for cryoEM. [[paper]](), [[bioRxiv]](https://www.biorxiv.org/content/10.1101/838920v1)

* **DeepEMhacer**: a deep learning solution for cryo-EM volume post-processing. [[paper]](https://www.biorxiv.org/content/10.1101/2020.06.12.148296v1?rss=1)

* **TranSPHIRE**: Automated and feedback-optimized on-the-fly processing for cryo-EM. [[paper]](https://www.biorxiv.org/content/10.1101/2020.06.16.155275v1?rss=1) 

* **Phenix.auto_sharpen**: Automated map sharpening by maximization of detail and connectivity. [[paper]](https://www.biorxiv.org/content/10.1101/247049v1.full.pdf) 

* **Phenix.density_modification**: Automated map sharpening by maximization of detail and connectivity. [[paper]](https://www.biorxiv.org/content/10.1101/845032v1) 

* **Deepsharpen**: Deep-Learning Based Sharpening Of 3D Reconstruction Map From Cryo-Electron Microscopy. [[paper]](https://ieeexplore.ieee.org/abstract/document/9153369/) 

* **SuperEM**: Super-Resolution Cryo-EM Maps With 3D Deep Generative Networks. [[paper]](https://www.biorxiv.org/content/10.1101/2021.01.12.426430v1) [[code]](https://github.com/kiharalab/SuperEM) [[webpage]](https://kiharalab.org/emsuites/superem.php) 



### Motion Correction

* Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM, [[paper]](http://www.nature.com/nmeth/journal/v10/n6/full/nmeth.2472.html).  



### 3D Reconstruction

* **Relion** - A Bayesian approach to refinement of 3D reconstructions or 2D class averages. [[webpage]](http://www2.mrc-lmb.cam.ac.uk/relion/index.php/Main_Page), [[code]](https://github.com/3dem/relion)

    * [Nature Protocol Paper](http://www.nature.com/nprot/journal/v11/n11/full/nprot.2016.124.html) - Resolving macromolecular structures from electron cryo-tomography data using subtomogram averaging in RELION

    * **2.1** [[code]](https://github.com/3dem/relion/releases/tag/2.1.0), [Tutorial (v2.1)](ftp://ftp.mrc-lmb.cam.ac.uk/pub/scheres/relion21_tutorial.pdf)

    * **3.0** - New tools for automated high-resolution cryo-EM structure determination in RELION-3. [[paper]](https://elifesciences.org/articles/42166) 

    * **externprior** - Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination. [[paper]](https://www.biorxiv.org/content/10.1101/2020.03.25.007914v1.full.pdf), [[code]](https://github.com/3dem/externprior) RELION external reconstruct functionality with a convolutional neural network.

    * **3.1** [[code]](https://github.com/3dem/relion/releases/tag/3.1.0), [Tutorial (v3.1)](ftp://ftp.mrc-lmb.cam.ac.uk/pub/scheres/relion31_tutorial.pdf)

    

* **cryoSPARC**: algorithms for rapid unsupervised cryo-EM structure determination. Nature Methods, 2017. [[paper]](http://www.nature.com/nmeth/journal/v14/n3/full/nmeth.4169.html)

* **THUNDER**: A particle-filter framework for robust cryo-EM 3D reconstruction. Nature Methods, 2018. [[paper]](https://www.nature.com/articles/s41592-018-0223-8) 

* **CryoDRGN** - Reconstructing continuously heterogeneous structures from single particle cryo-EM with deep generative models. ICLR 2020(spotlight). [[paper]](https://arxiv.org/pdf/1909.05215).

* **CryoGAN**: A New Reconstruction Paradigm for Single-particle Cryo-EM Via Deep Adversarial Learning. [[paper]](https://www.biorxiv.org/content/10.1101/2020.03.20.001016v1).



### Model Building



* **PHENIX** - Automated determination of molecular structures using X-ray crystallography and other methods. [[webpage]]((https://www.phenix-online.org/)).

    * Map_to_model - A fully automatic method yielding initial models from high-resolution electron cryo-microscopy.  Nature Methods, 2018. [[paper]](https://www.nature.com/articles/s41592-018-0173-1), [[bioRxiv]](https://www.biorxiv.org/content/biorxiv/early/2018/02/16/267138.full.pdf).

* **Rosetta** - A software suite includes algorithms for computational modeling and analysis of protein structures. [[webpage]](https://www.rosettacommons.org/).

    * **RosettaCM** - High-Resolution Comparative Modeling with RosettaCM. [[paper]](http://www.sciencedirect.com/science/article/pii/S0969212613002979?via%3Dihub).

    * De novo protein structure determination from near-atomic-resolution cryo-EM maps. Nature Methods, 2015. [[paper]](http://www.nature.com/doifinder/10.1038/nmeth.3287).

    * Atomic accuracy models from 4.5 Å cryo-electron microscopy data with density-guided iterative local refinement. Nature Methods, 2015. [[paper]](http://www.nature.com/doifinder/10.1038/nmeth.3286).

    * RosettaES: a sampling strategy enabling automated interpretation of difficult cryo-EM maps. Nature Methods, 2017. [[paper]](http://www.nature.com/nmeth/journal/v14/n8/full/nmeth.4340.html).

* **ISOLDE** - Ease the task of model building at low resolution. [[webpage]](https://isolde.cimr.cam.ac.uk/).

* **EMfold** - Placement of helices is restricted to CryoEM density regions. [[webpage]]((http://www.meilerlab.org/index.php/servers/show?s_id=18) )

* **Pathwalker** - Constructing and Validating Initial Cα Models from Subnanometer Resolution Density Maps with Pathwalking. [[paper]](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3307788/pdf/nihms350767.pdf).

* **EMBuilder**: A Template Matching-based Automatic Model-building Program for High-resolution Cryo-Electron Microscopy Maps. [[paper]](https://www.nature.com/articles/s41598-017-02725-w).

* Tools for Model Building and Optimization into Near-Atomic Resolution Electron Cryo-Microscopy Density Maps. [[Book chapter]](https://www.sciencedirect.com/science/article/pii/S0076687916301136?via%3Dihub).

* **MAINMAST** - De novo main-chain modeling for EM maps using MAINMAST. [[paper]](https://www.nature.com/articles/s41467-018-04053-7), [[webpage]](http://kiharalab.org/mainmast/).

* **A^2-Net**: Molecular Structure Estimation from Cryo-EM Density Volumes. The 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019. [[paper]](https://arxiv.org/abs/1901.00785), [[webpage]](http://zhanglab.net/A-2-Net).

* **Cascaded-CNN**: Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps. [[paper]](https://www.biorxiv.org/content/10.1101/572990v3), [[code]](https://github.com/DrDongSi/Ca-Backbone-Prediction).

* **DeepTracer**: Predicting Backbone Atomic Structure from High Resolution Cryo-EM Density Maps of Protein Complexes. [[paper]](https://www.biorxiv.org/content/10.1101/2020.02.12.946772v1), [[paper2]](https://www.biorxiv.org/content/10.1101/2020.07.21.214064v2), [[web service]](https://deeptracer.uw.edu/).

* **MSTree** - Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution. [[paper]](https://www.biorxiv.org/content/10.1101/2020.01.03.893669v1.full.pdf).

* **Haruspex** - Automatic annotation of Cryo-EM maps with the convolutional neural network. [[paper]](https://www.biorxiv.org/content/10.1101/644476v3.full.pdf).

* Scipion - Integration of Cryo-EM Model Building Software in Scipion, 2020. [[paper]](https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.9b01032), [[webpage]](http://scipion.i2pc.es), [[code]](https://github.com/I2PC/scipion).



### Refinement

[back to top](#readme) 



* Phenix.real_space_refinement

* REFMAC

* ProSMART - reference restraints for proteins and nucleic acids

* LIBG - base-pair and parallelization restraints

* Rosetta

* EM-fit

* MDFF, molecular dynamics flexible fitting

* DireX



## Structure Validation 

[back to top](#readme) 



* **Molprobity**

* **EMRinger**: side chain–directed model and map validation for 3D cryo-electron microscopy. [[paper]](https://www.nature.com/articles/nmeth.3541), [[code]](https://github.com/fraser-lab/EMRinger).

* [RMSD](https://en.wikipedia.org/wiki/Root-mean-square_deviation_of_atomic_positions) - Root Mean Square Deviation

* [FSC](https://en.wikipedia.org/wiki/Fourier_shell_correlation) - Fourier shell correlation.

* [B-factor](http://www.cmbi.ru.nl/bdb/theory/) -  A measure of (local) mobility in the (macro)molecule.

* [GDT-HA](http://onlinelibrary.wiley.com/doi/10.1002/prot.21753/full) - The percentage of correctly aligned residues in the 5 Å LGA sequence-independent superposition of the model and experimental structure of the target.

* [GDT-TS](#)

* [AL0](#)



### Other Related Research/Tools

* **ResMap** - computing the local resolution of 3D density maps, 2013. [[paper]](https://www.nature.com/articles/nmeth.2727), [[code]](http://resmap.sourceforge.net/),[[code-python3+variant-shape]](https://github.com/kuixu/ResMap) 

*Automated Threshold Selection for Cryo-EM Density Maps. [[paper]](https://www.biorxiv.org/content/biorxiv/early/2019/06/02/657395.full.pdf)

* Extraction of Protein Dynamics Information Hidden in Cryo-EM Map Using Deep Learning, 2020.  [[paper]](https://www.biorxiv.org/content/10.1101/2020.02.17.951863v1), [[code]](https://github.com/clinfo/DEFMap)

* **MicrographCleaner**: a python package for cryo-EM micrograph cleaning using deep learning, [[paper]](https://www.biorxiv.org/content/10.1101/677542v3) - 

* Deep Learning for Validating and Estimating Resolution of Cryo-Electron Microscopy Density Maps. [[paper]](https://doi.org/10.3390/molecules24061181) 



### Tomography

* **EMAN2** - A scientific image processing software suite with a focus on CryoEM and CryoET. [[webpage]]((http://blake.bcm.edu/emanwiki/EMAN2)), [[code]](https://github.com/cryoem/eman2).

    * CryoET Segmentation - Convolutional Neural Networks for Automated Annotation of Cellular CryoElectron Tomograms. [[paper]](https://www.nature.com/nmeth/journal/v14/n10/full/nmeth.4405.html), [[arxiv]](https://arxiv.org/pdf/1701.05567.pdf)

* Subtomogram Subdivision, Deep learning based subdivision approach for large scale macromolecules

structure recovery from electron cryo tomograms. [[paper]](https://arxiv.org/pdf/1701.08404.pdf)

* **pytom**. [[webpage]](http://pytom.org/),  [[Tutorial]](http://pytom.org/doc/pytom/tutorial.html) 

* **emClarity**: software for high-resolution cryo-electron tomography and subtomogram averaging. [[paper]](http://dx.doi.org/10.1038/s41592-018-0167-z), [[code]](https://github.com/bHimes/emClarity), [[wiki]](https://github.com/bHimes/emClarity/wiki)



## DataBases

[back to top](#readme) 



* [EMDB](https://www.ebi.ac.uk/pdbe/emdb/index.html) - The Electron Microscopy Data Bank (EMDB)

* [EMPIAR](https://www.ebi.ac.uk/pdbe/emdb/empiar) - EMPIAR, the Electron Microscopy Pilot Image Archive, is a public resource for raw, 2D electron microscopy images.

    * [EMPIAR: a public archive for raw electron microscopy image data](http://www.nature.com/doifinder/10.1038/nmeth.3806)

* [PDB](http://www.rcsb.org/pdb/home/home.do) - Protein Data Bank

* [PDBe](http://www.ebi.ac.uk/pdbe) - Protein Data Bank in Europe

* [PDBj](http://www.pdbj.org) - Protein Data Bank Japan 

* [wwPDB](http://www.wwpdb.org) - WorldWide Protein Data Bank 

* [sbkb](http://www.sbkb.org) - Structural Biology Knowledgebase, A comprehensive resource for developments both in structural genomics and structural biology.



## Active Groups



* [MRC](http://www2.mrc-lmb.cam.ac.uk/).

    * [Richard Henderson](http://www2.mrc-lmb.cam.ac.uk/group-leaders/h-to-m/richard-henderson/).

    * [Scheres](http://www2.mrc-lmb.cam.ac.uk/groups/scheres/). 

* [Joachim Frank](http://franklab.cpmc.columbia.edu/franklab).

* [Bob Glaeser](http://mcb.berkeley.edu/faculty/all/glaeserr).

* [Yifan Cheng](http://cryoem.ucsf.edu/).

* [Yigong Shi](http://ygshi.life.tsinghua.edu.cn/home.htm).

* [Eva Nogales](http://cryoem.berkeley.edu/). 

* [David Baker](http://www.ipd.uw.edu/people/ipd-faculty-staff/david-baker/).

* [Frank DiMaio](https://faculty.washington.edu/dimaio/wordpress/).

* [Xueming Li](http://life.tsinghua.edu.cn/faculty/faculty/2730.html).

* [Hong-wei Wang](http://cryoem.life.tsinghua.edu.cn).

* [Marcus Brubakero](http://www.cs.toronto.edu/~mbrubake/).

* [Meiler Lab](http://www.meilerlab.org/index.php).

* [Sriram Subramaniam](https://electron.med.ubc.ca/).

* [Michael Cianfrocco Lab](http://www.lsi.umich.edu/labs/michael-cianfrocco-lab).

* [Kihara Lab](http://kiharalab.org/mainmast/).

* [Bonnie Berger](http://people.csail.mit.edu/bab/).



[3D-EM Laboratories](http://3dem.ucsd.edu/labs_a_c.shtm)



## Workshop Docs



* [EMAN2 ](http://blake.bcm.edu/emanwiki/EMAN2/Tutorials)

* [Resource from Meiler Lab](http://www.meilerlab.org/index.php/jobs/resources) - Rosetta Tutorials, Teaching Resources, etc.



## Websites



* [Software Tools For Molecular Microscopy](http://en.wikibooks.org/wiki/Software_Tools_For_Molecular_Microscopy)



## License



[![CC0](http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)](https://creativecommons.org/publicdomain/zero/1.0/)