Supported Applications

cryoDRGN

Description

a neural network based algorithm for heterogeneous cryo-EM reconstruction. In particular, the method models a continuous distribution over 3D structures by using a neural network based representation for the volume.
Usage
To list all executables provided by cryoDRGN, run: $ sbgrid-list cryodrgn
Installation
Use the following command to install this title with the CLI client: $ sbgrid-cli install cryodrgn Available operating systems: Linux 64
Primary Citation*

E. D. Zhong, T. Bepler, B. Berger, and J. H. Davis. 2021. CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks. Nature methods. 18(2): 176-185.
- *Full citation information available through
Citation Note

Uncovering structural ensembles from single particle cryo-EM data using cryoDRGN.
Laurel Kinman, Barrett Powell, Ellen Zhong*, Bonnie Berger*, Joey Davis*
Nature Protocols 2023.

CryoDRGN: Reconstruction of heterogeneous cryo-EM structures using neural networks.
Ellen D. Zhong, Tristan Bepler, Bonnie Berger*, Joseph H Davis*
Nature Methods 2021.

Reconstructing continuous distributions of 3D protein structure from cryo-EM images.
Ellen D. Zhong, Tristan Bepler, Joseph H. Davis*, Bonnie Berger*
ICLR 2020.
Webinars

Topic: CryoDRGN: Deep generative models for reconstructing heterogeneous protein structures from cryo-EM
Speaker: Ellen Zhong, MIT, Laboratories of Bonnie Berger and Joey Davis

Host: Shaun Rawson
Recorded on: May 15, 2020