Multi-omic data integration enables discovery of hidden biological regularities

Translating omics data sets into biological insight is one of the great challenges of our time. Here, the authors make headway by synchronising pairs of omics data types via invariants across conditions and by integrating datasets into a genome-scale model of E. coli metabolism and gene expression.

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Autores principales:	Ali Ebrahim, Elizabeth Brunk, Justin Tan, Edward J. O'Brien, Donghyuk Kim, Richard Szubin, Joshua A. Lerman, Anna Lechner, Anand Sastry, Aarash Bordbar, Adam M. Feist, Bernhard O. Palsson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2016
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/54b0e226f9794904895aa0e7518d169f
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spelling	oai:doaj.org-article:54b0e226f9794904895aa0e7518d169f2021-12-02T17:33:20ZMulti-omic data integration enables discovery of hidden biological regularities10.1038/ncomms130912041-1723https://doaj.org/article/54b0e226f9794904895aa0e7518d169f2016-10-01T00:00:00Zhttps://doi.org/10.1038/ncomms13091https://doaj.org/toc/2041-1723Translating omics data sets into biological insight is one of the great challenges of our time. Here, the authors make headway by synchronising pairs of omics data types via invariants across conditions and by integrating datasets into a genome-scale model of E. coli metabolism and gene expression.Ali EbrahimElizabeth BrunkJustin TanEdward J. O'BrienDonghyuk KimRichard SzubinJoshua A. LermanAnna LechnerAnand SastryAarash BordbarAdam M. FeistBernhard O. PalssonNature PortfolioarticleScienceQENNature Communications, Vol 7, Iss 1, Pp 1-9 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Ali Ebrahim Elizabeth Brunk Justin Tan Edward J. O'Brien Donghyuk Kim Richard Szubin Joshua A. Lerman Anna Lechner Anand Sastry Aarash Bordbar Adam M. Feist Bernhard O. Palsson Multi-omic data integration enables discovery of hidden biological regularities
description	Translating omics data sets into biological insight is one of the great challenges of our time. Here, the authors make headway by synchronising pairs of omics data types via invariants across conditions and by integrating datasets into a genome-scale model of E. coli metabolism and gene expression.
format	article
author	Ali Ebrahim Elizabeth Brunk Justin Tan Edward J. O'Brien Donghyuk Kim Richard Szubin Joshua A. Lerman Anna Lechner Anand Sastry Aarash Bordbar Adam M. Feist Bernhard O. Palsson
author_facet	Ali Ebrahim Elizabeth Brunk Justin Tan Edward J. O'Brien Donghyuk Kim Richard Szubin Joshua A. Lerman Anna Lechner Anand Sastry Aarash Bordbar Adam M. Feist Bernhard O. Palsson
author_sort	Ali Ebrahim
title	Multi-omic data integration enables discovery of hidden biological regularities
title_short	Multi-omic data integration enables discovery of hidden biological regularities
title_full	Multi-omic data integration enables discovery of hidden biological regularities
title_fullStr	Multi-omic data integration enables discovery of hidden biological regularities
title_full_unstemmed	Multi-omic data integration enables discovery of hidden biological regularities
title_sort	multi-omic data integration enables discovery of hidden biological regularities
publisher	Nature Portfolio
publishDate	2016
url	https://doaj.org/article/54b0e226f9794904895aa0e7518d169f
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Multi-omic data integration enables discovery of hidden biological regularities

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