cryoDRGN 0.3.5-foss-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-foss-2020b

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

📋 module load cryoDRGN/0.3.5-foss-2020b

BEAR Apps Version

2020b

Architectures

EL8-cascadelake — EL8-icelake — EL8-sapphirerapids

The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.

Extensions

• 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.

Dependencies

This version of cryoDRGN has a direct dependency on: foss/2020b IPython/7.18.1-GCCcore-10.2.0 JupyterLab/2.2.8-GCCcore-10.2.0 matplotlib/3.3.3-foss-2020b numba/0.52.0-foss-2020b plotly.py/4.14.3-GCCcore-10.2.0 Python/3.8.6-GCCcore-10.2.0 PyTorch/1.7.1-foss-2020b scikit-learn/0.23.2-foss-2020b SciPy-bundle/2020.11-foss-2020b Seaborn/0.11.1-foss-2020b

Last modified on 6th May 2022