Inferring time derivatives including cell growth rates using Gaussian processes

High-throughput time-series data is increasingly available, yet estimating time-derivatives from such data can remain a challenge. Here, the authors provide a non-parametric method for inferring the first and second time-derivatives from multiple replicates of time-series data and for estimating err...

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Autores principales:	Peter S. Swain, Keiran Stevenson, Allen Leary, Luis F. Montano-Gutierrez, Ivan B.N. Clark, Jackie Vogel, Teuta Pilizota
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2016
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/6aefe21cd35443ab9d0e44b3d219f660
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spelling	oai:doaj.org-article:6aefe21cd35443ab9d0e44b3d219f6602021-12-02T15:35:45ZInferring time derivatives including cell growth rates using Gaussian processes10.1038/ncomms137662041-1723https://doaj.org/article/6aefe21cd35443ab9d0e44b3d219f6602016-12-01T00:00:00Zhttps://doi.org/10.1038/ncomms13766https://doaj.org/toc/2041-1723High-throughput time-series data is increasingly available, yet estimating time-derivatives from such data can remain a challenge. Here, the authors provide a non-parametric method for inferring the first and second time-derivatives from multiple replicates of time-series data and for estimating errors in this inference and in any summary statistics.Peter S. SwainKeiran StevensonAllen LearyLuis F. Montano-GutierrezIvan B.N. ClarkJackie VogelTeuta PilizotaNature PortfolioarticleScienceQENNature Communications, Vol 7, Iss 1, Pp 1-8 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Peter S. Swain Keiran Stevenson Allen Leary Luis F. Montano-Gutierrez Ivan B.N. Clark Jackie Vogel Teuta Pilizota Inferring time derivatives including cell growth rates using Gaussian processes
description	High-throughput time-series data is increasingly available, yet estimating time-derivatives from such data can remain a challenge. Here, the authors provide a non-parametric method for inferring the first and second time-derivatives from multiple replicates of time-series data and for estimating errors in this inference and in any summary statistics.
format	article
author	Peter S. Swain Keiran Stevenson Allen Leary Luis F. Montano-Gutierrez Ivan B.N. Clark Jackie Vogel Teuta Pilizota
author_facet	Peter S. Swain Keiran Stevenson Allen Leary Luis F. Montano-Gutierrez Ivan B.N. Clark Jackie Vogel Teuta Pilizota
author_sort	Peter S. Swain
title	Inferring time derivatives including cell growth rates using Gaussian processes
title_short	Inferring time derivatives including cell growth rates using Gaussian processes
title_full	Inferring time derivatives including cell growth rates using Gaussian processes
title_fullStr	Inferring time derivatives including cell growth rates using Gaussian processes
title_full_unstemmed	Inferring time derivatives including cell growth rates using Gaussian processes
title_sort	inferring time derivatives including cell growth rates using gaussian processes
publisher	Nature Portfolio
publishDate	2016
url	https://doaj.org/article/6aefe21cd35443ab9d0e44b3d219f660
work_keys_str_mv	AT petersswain inferringtimederivativesincludingcellgrowthratesusinggaussianprocesses AT keiranstevenson inferringtimederivativesincludingcellgrowthratesusinggaussianprocesses AT allenleary inferringtimederivativesincludingcellgrowthratesusinggaussianprocesses AT luisfmontanogutierrez inferringtimederivativesincludingcellgrowthratesusinggaussianprocesses AT ivanbnclark inferringtimederivativesincludingcellgrowthratesusinggaussianprocesses AT jackievogel inferringtimederivativesincludingcellgrowthratesusinggaussianprocesses AT teutapilizota inferringtimederivativesincludingcellgrowthratesusinggaussianprocesses
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Inferring time derivatives including cell growth rates using Gaussian processes

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