Learning dynamical information from static protein and sequencing data

Reconstructing system dynamics on complex high-dimensional energy landscapes from static experimental snapshots remains challenging. Here, the authors introduce a framework to infer the essential dynamics of physical and biological systems without need for time-dependent measurements.

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Autores principales:	Philip Pearce, Francis G. Woodhouse, Aden Forrow, Ashley Kelly, Halim Kusumaatmaja, Jörn Dunkel
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/ea15b726de5c44c49d48fefe125fa6ad
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spelling	oai:doaj.org-article:ea15b726de5c44c49d48fefe125fa6ad2021-12-02T17:02:16ZLearning dynamical information from static protein and sequencing data10.1038/s41467-019-13307-x2041-1723https://doaj.org/article/ea15b726de5c44c49d48fefe125fa6ad2019-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-13307-xhttps://doaj.org/toc/2041-1723Reconstructing system dynamics on complex high-dimensional energy landscapes from static experimental snapshots remains challenging. Here, the authors introduce a framework to infer the essential dynamics of physical and biological systems without need for time-dependent measurements.Philip PearceFrancis G. WoodhouseAden ForrowAshley KellyHalim KusumaatmajaJörn DunkelNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-8 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Philip Pearce Francis G. Woodhouse Aden Forrow Ashley Kelly Halim Kusumaatmaja Jörn Dunkel Learning dynamical information from static protein and sequencing data
description	Reconstructing system dynamics on complex high-dimensional energy landscapes from static experimental snapshots remains challenging. Here, the authors introduce a framework to infer the essential dynamics of physical and biological systems without need for time-dependent measurements.
format	article
author	Philip Pearce Francis G. Woodhouse Aden Forrow Ashley Kelly Halim Kusumaatmaja Jörn Dunkel
author_facet	Philip Pearce Francis G. Woodhouse Aden Forrow Ashley Kelly Halim Kusumaatmaja Jörn Dunkel
author_sort	Philip Pearce
title	Learning dynamical information from static protein and sequencing data
title_short	Learning dynamical information from static protein and sequencing data
title_full	Learning dynamical information from static protein and sequencing data
title_fullStr	Learning dynamical information from static protein and sequencing data
title_full_unstemmed	Learning dynamical information from static protein and sequencing data
title_sort	learning dynamical information from static protein and sequencing data
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/ea15b726de5c44c49d48fefe125fa6ad
work_keys_str_mv	AT philippearce learningdynamicalinformationfromstaticproteinandsequencingdata AT francisgwoodhouse learningdynamicalinformationfromstaticproteinandsequencingdata AT adenforrow learningdynamicalinformationfromstaticproteinandsequencingdata AT ashleykelly learningdynamicalinformationfromstaticproteinandsequencingdata AT halimkusumaatmaja learningdynamicalinformationfromstaticproteinandsequencingdata AT jorndunkel learningdynamicalinformationfromstaticproteinandsequencingdata
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Learning dynamical information from static protein and sequencing data

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