cryoDRGN 0.3.5-foss-2020bcryoDRGN: 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, BEARCloud VMs, and CaStLeS VMs):
module load cryoDRGN/0.3.5-foss-2020b
There is a GPU enabled version of this module: cryoDRGN 0.3.5-fosscuda-2020b
BEAR Apps Version
- colorlover 0.3.0
- cryodrgn 0.3.5
- cufflinks 0.17.3
- pynndescent 0.5.2
For more information visit the cryoDRGN website.
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
These versions of cryoDRGN are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.
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Last modified on 6th May 2022