DeepEMhancer: a deep learning solution for cryo-EM volume post-processing

Cryo-EM maps are valuable sources of information for protein structure modeling. However, due to the loss of contrast at high frequencies, they generally need to be post-processed to improve their interpretability. Most popular approaches, based on global B-factor correction, suffer from limitations...

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Detalles Bibliográficos
Autores principales: Sanchez-Garcia, Ruben, Gomez-Blanco, Josue, Cuervo, Ana, Carazo, Jose Maria, Sorzano, Carlos Oscar S., Vargas, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282847/
https://www.ncbi.nlm.nih.gov/pubmed/34267316
http://dx.doi.org/10.1038/s42003-021-02399-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282847/
https://www.ncbi.nlm.nih.gov/pubmed/34267316
http://dx.doi.org/10.1038/s42003-021-02399-1

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