Inferring the molecular and phenotypic impact of amino acid variants with MutPred2

Identifying variants capable of causing genetic disease is challenging. The authors use semisupervised learning to predict pathogenic missense variants and their impacts on protein structure and function, enabling a molecular mechanism-driven approach to studying different types of human disease.

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Detalles Bibliográficos
Autores principales:	Vikas Pejaver, Jorge Urresti, Jose Lugo-Martinez, Kymberleigh A. Pagel, Guan Ning Lin, Hyun-Jun Nam, Matthew Mort, David N. Cooper, Jonathan Sebat, Lilia M. Iakoucheva, Sean D. Mooney, Predrag Radivojac
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/1e05d841d70843dea427e050f3dbb928
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spelling	oai:doaj.org-article:1e05d841d70843dea427e050f3dbb9282021-12-02T14:42:16ZInferring the molecular and phenotypic impact of amino acid variants with MutPred210.1038/s41467-020-19669-x2041-1723https://doaj.org/article/1e05d841d70843dea427e050f3dbb9282020-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-19669-xhttps://doaj.org/toc/2041-1723Identifying variants capable of causing genetic disease is challenging. The authors use semisupervised learning to predict pathogenic missense variants and their impacts on protein structure and function, enabling a molecular mechanism-driven approach to studying different types of human disease.Vikas PejaverJorge UrrestiJose Lugo-MartinezKymberleigh A. PagelGuan Ning LinHyun-Jun NamMatthew MortDavid N. CooperJonathan SebatLilia M. IakouchevaSean D. MooneyPredrag RadivojacNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-13 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Vikas Pejaver Jorge Urresti Jose Lugo-Martinez Kymberleigh A. Pagel Guan Ning Lin Hyun-Jun Nam Matthew Mort David N. Cooper Jonathan Sebat Lilia M. Iakoucheva Sean D. Mooney Predrag Radivojac Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
description	Identifying variants capable of causing genetic disease is challenging. The authors use semisupervised learning to predict pathogenic missense variants and their impacts on protein structure and function, enabling a molecular mechanism-driven approach to studying different types of human disease.
format	article
author	Vikas Pejaver Jorge Urresti Jose Lugo-Martinez Kymberleigh A. Pagel Guan Ning Lin Hyun-Jun Nam Matthew Mort David N. Cooper Jonathan Sebat Lilia M. Iakoucheva Sean D. Mooney Predrag Radivojac
author_facet	Vikas Pejaver Jorge Urresti Jose Lugo-Martinez Kymberleigh A. Pagel Guan Ning Lin Hyun-Jun Nam Matthew Mort David N. Cooper Jonathan Sebat Lilia M. Iakoucheva Sean D. Mooney Predrag Radivojac
author_sort	Vikas Pejaver
title	Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
title_short	Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
title_full	Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
title_fullStr	Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
title_full_unstemmed	Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
title_sort	inferring the molecular and phenotypic impact of amino acid variants with mutpred2
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/1e05d841d70843dea427e050f3dbb928
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Inferring the molecular and phenotypic impact of amino acid variants with MutPred2

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