cryoDRGN 0.3.5-fosscuda-2020b

cryoDRGN: Deep Reconstructing Generative Networks for cryo-EM heterogeneous reconstruction. CryoDRGN is 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.

Accessing cryoDRGN 0.3.5-fosscuda-2020b

To load the module for cryoDRGN 0.3.5-fosscuda-2020b please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load cryoDRGN/0.3.5-fosscuda-2020b

There is a CPU version of this module: cryoDRGN 0.3.5-foss-2020b

BEAR Apps Version



  • colorlover 0.3.0
  • cryodrgn 0.3.5
  • cufflinks 0.17.3
  • pynndescent 0.5.2
  • umap-learn-0.5.1

More Information

For more information visit the cryoDRGN website.


This version of cryoDRGN has a direct dependency on: fosscuda/2020b IPython/7.18.1-GCCcore-10.2.0 JupyterLab/2.2.8-GCCcore-10.2.0 matplotlib/3.3.3-fosscuda-2020b numba/0.52.0-fosscuda-2020b Python/3.8.6-GCCcore-10.2.0 PyTorch/1.7.1-fosscuda-2020b scikit-learn/0.23.2-fosscuda-2020b SciPy-bundle/2020.11-fosscuda-2020b Seaborn/0.11.1-fosscuda-2020b

Other Versions

These versions of cryoDRGN are available on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Version BEAR Apps Version
0.3.5-foss-2020b 2020b

Last modified on 6th May 2022