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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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Vydáno v:BMC Bioinformatics
Hlavní autoři: Fukuda, Hiroyuki, Tomii, Kentaro
Médium: Artigo
Jazyk:Inglês
Vydáno: BioMed Central 2020
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC6953294/
https://ncbi.nlm.nih.gov/pubmed/31918654
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-019-3190-x
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