CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction

Protein structure prediction is a challenge. A new deep learning framework, CopulaNet, is a major step forward toward end-to-end prediction of inter-residue distances and protein tertiary structures with improved accuracy and efficiency.

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Autores principales:	Fusong Ju, Jianwei Zhu, Bin Shao, Lupeng Kong, Tie-Yan Liu, Wei-Mou Zheng, Dongbo Bu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/33cc2239e1a44129b8b0dddfeb060858
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id	oai:doaj.org-article:33cc2239e1a44129b8b0dddfeb060858
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spelling	oai:doaj.org-article:33cc2239e1a44129b8b0dddfeb0608582021-12-02T16:49:12ZCopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction10.1038/s41467-021-22869-82041-1723https://doaj.org/article/33cc2239e1a44129b8b0dddfeb0608582021-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-22869-8https://doaj.org/toc/2041-1723Protein structure prediction is a challenge. A new deep learning framework, CopulaNet, is a major step forward toward end-to-end prediction of inter-residue distances and protein tertiary structures with improved accuracy and efficiency.Fusong JuJianwei ZhuBin ShaoLupeng KongTie-Yan LiuWei-Mou ZhengDongbo BuNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Fusong Ju Jianwei Zhu Bin Shao Lupeng Kong Tie-Yan Liu Wei-Mou Zheng Dongbo Bu CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction
description	Protein structure prediction is a challenge. A new deep learning framework, CopulaNet, is a major step forward toward end-to-end prediction of inter-residue distances and protein tertiary structures with improved accuracy and efficiency.
format	article
author	Fusong Ju Jianwei Zhu Bin Shao Lupeng Kong Tie-Yan Liu Wei-Mou Zheng Dongbo Bu
author_facet	Fusong Ju Jianwei Zhu Bin Shao Lupeng Kong Tie-Yan Liu Wei-Mou Zheng Dongbo Bu
author_sort	Fusong Ju
title	CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction
title_short	CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction
title_full	CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction
title_fullStr	CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction
title_full_unstemmed	CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction
title_sort	copulanet: learning residue co-evolution directly from multiple sequence alignment for protein structure prediction
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/33cc2239e1a44129b8b0dddfeb060858
work_keys_str_mv	AT fusongju copulanetlearningresiduecoevolutiondirectlyfrommultiplesequencealignmentforproteinstructureprediction AT jianweizhu copulanetlearningresiduecoevolutiondirectlyfrommultiplesequencealignmentforproteinstructureprediction AT binshao copulanetlearningresiduecoevolutiondirectlyfrommultiplesequencealignmentforproteinstructureprediction AT lupengkong copulanetlearningresiduecoevolutiondirectlyfrommultiplesequencealignmentforproteinstructureprediction AT tieyanliu copulanetlearningresiduecoevolutiondirectlyfrommultiplesequencealignmentforproteinstructureprediction AT weimouzheng copulanetlearningresiduecoevolutiondirectlyfrommultiplesequencealignmentforproteinstructureprediction AT dongbobu copulanetlearningresiduecoevolutiondirectlyfrommultiplesequencealignmentforproteinstructureprediction
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CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction

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