DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment

BACKGROUND: Recently developed methods of protein contact prediction, a crucially important step for protein structure prediction, depend heavily on deep neural networks (DNNs) and multiple sequence alignments (MSAs) of target proteins. Protein sequences are accumulating to an increasing degree such...

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Detalles Bibliográficos
Autores principales: Fukuda, Hiroyuki, Tomii, Kentaro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953294/
https://www.ncbi.nlm.nih.gov/pubmed/31918654
http://dx.doi.org/10.1186/s12859-019-3190-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953294/
https://www.ncbi.nlm.nih.gov/pubmed/31918654
http://dx.doi.org/10.1186/s12859-019-3190-x

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