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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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| Publicado en: | BMC Bioinformatics |
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| Autores principales: | , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
BioMed Central
2020
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| Materias: | |
| Acceso en línea: | 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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