Topaz 0.2.4-foss-2020b-PyTorch-1.7.1

Pipeline for particle picking in cryo-electron microscopy images using convolutional neural networks trained from positive and unlabeled examples. Also featuring micrograph and tomogram denoising with DNNs.

Accessing Topaz 0.2.4-foss-2020b-PyTorch-1.7.1

To load the module for Topaz 0.2.4-foss-2020b-PyTorch-1.7.1 please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load Topaz/0.2.4-foss-2020b-PyTorch-1.7.1

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.

More Information

For more information visit the Topaz website.

Dependencies

This version of Topaz has a direct dependency on: foss/2020b Python/3.8.6-GCCcore-10.2.0 PyTorch/1.7.1-foss-2020b scikit-learn/0.23.2-foss-2020b torchvision/0.8.2-foss-2020b-PyTorch-1.7.1

Last modified on 13th July 2021