Supported Applications

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

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

Primary Citation*

R. Sanchez-Garcia, J. Gomez-Blanco, A. Cuervo, J. M. Carazo, C. O. S. Sorzano, and J. Vargas. 2021. DeepEMhancer: a deep learning solution for cryo-EM volume post-processing. Communications Biology. 4(1): 874.

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  *Full citation information available through

• AppCiter

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