VAMPnets for deep learning of molecular kinetics

Extracting kinetic models from high-throughput molecular dynamics (MD) simulations is laborious and prone to human error. Here the authors introduce a deep learning framework that automates construction of Markov state models from MD simulation data.

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Detalles Bibliográficos
Autores principales:	Andreas Mardt, Luca Pasquali, Hao Wu, Frank Noé
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/8a30e6ffd9b7407e84418e912a435af9
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spelling	oai:doaj.org-article:8a30e6ffd9b7407e84418e912a435af92021-12-02T15:34:19ZVAMPnets for deep learning of molecular kinetics10.1038/s41467-017-02388-12041-1723https://doaj.org/article/8a30e6ffd9b7407e84418e912a435af92018-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-02388-1https://doaj.org/toc/2041-1723Extracting kinetic models from high-throughput molecular dynamics (MD) simulations is laborious and prone to human error. Here the authors introduce a deep learning framework that automates construction of Markov state models from MD simulation data.Andreas MardtLuca PasqualiHao WuFrank NoéNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-11 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Andreas Mardt Luca Pasquali Hao Wu Frank Noé VAMPnets for deep learning of molecular kinetics
description	Extracting kinetic models from high-throughput molecular dynamics (MD) simulations is laborious and prone to human error. Here the authors introduce a deep learning framework that automates construction of Markov state models from MD simulation data.
format	article
author	Andreas Mardt Luca Pasquali Hao Wu Frank Noé
author_facet	Andreas Mardt Luca Pasquali Hao Wu Frank Noé
author_sort	Andreas Mardt
title	VAMPnets for deep learning of molecular kinetics
title_short	VAMPnets for deep learning of molecular kinetics
title_full	VAMPnets for deep learning of molecular kinetics
title_fullStr	VAMPnets for deep learning of molecular kinetics
title_full_unstemmed	VAMPnets for deep learning of molecular kinetics
title_sort	vampnets for deep learning of molecular kinetics
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/8a30e6ffd9b7407e84418e912a435af9
work_keys_str_mv	AT andreasmardt vampnetsfordeeplearningofmolecularkinetics AT lucapasquali vampnetsfordeeplearningofmolecularkinetics AT haowu vampnetsfordeeplearningofmolecularkinetics AT franknoe vampnetsfordeeplearningofmolecularkinetics
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VAMPnets for deep learning of molecular kinetics

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