Supported Applications

DeepEMhancer

Description

(Deep cryo-EM Map Enhancer) a python package designed to perform non-linear post-processing of cryo-EM maps for local sharpening, automatic masking and denoising. Systems using cuda 11+ should use the 20210511 version of deepEMhancer, and the modified models distributed in /programs/share/deepemhancer/20210511/deepEMhancerModels/production_checkpoints/
Usage Notes

Known Issues:
Users have reported issues when loading the models obtained using the --download flag with DeepEMhancer. If you have errors running the application, try adding this flag

--deepLearningModelPath /programs/share/deepemhancer/20210511/deepEMhancerModels/production_checkpoints

to your deepemhancer command. This will use the local models which are known to work with the versions of DeepEMhancer in SBGrid.
Installation
Use the following command to install this title with the CLI client: $ sbgrid-cli install deepemhancer
Primary Citation*

R. Sanchez-Garcia, J. Gomez-Blanco, A. Cuervo, J. M. Carazo, C. O. S. Sorzano, and J. Vargas. 2020. DeepEMhancer: a deep learning solution for cryo-EM volume post-processing. bioRxiv. 2020.06.12.148296.
- *Full citation information available through
Webinars

Topic: DeepEMhancer: exploiting previous knowledge to enhance map visualization
Presenter: Rubén Sánchez Garcia, Ph.D., The National Centre for Biotechnolgy, Spanish National Research Council

Host: Pete Meyer
Recorded on January 26, 2021