Predicting the evolution of Escherichia coli by a data-driven approach

How reproducible evolutionary processes are remains an important question in evolutionary biology. Here, the authors compile a compendium of more than 15,000 mutation events for Escherichia coli under 178 distinct environmental settings, and develop an ensemble of predictors to predict evolution at...

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Autores principales:	Xiaokang Wang, Violeta Zorraquino, Minseung Kim, Athanasios Tsoukalas, Ilias Tagkopoulos
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/3d716d97abf6460ea0ada536a16d3e36
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spelling	oai:doaj.org-article:3d716d97abf6460ea0ada536a16d3e362021-12-02T14:41:16ZPredicting the evolution of Escherichia coli by a data-driven approach10.1038/s41467-018-05807-z2041-1723https://doaj.org/article/3d716d97abf6460ea0ada536a16d3e362018-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-05807-zhttps://doaj.org/toc/2041-1723How reproducible evolutionary processes are remains an important question in evolutionary biology. Here, the authors compile a compendium of more than 15,000 mutation events for Escherichia coli under 178 distinct environmental settings, and develop an ensemble of predictors to predict evolution at a gene level.Xiaokang WangVioleta ZorraquinoMinseung KimAthanasios TsoukalasIlias TagkopoulosNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-12 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Xiaokang Wang Violeta Zorraquino Minseung Kim Athanasios Tsoukalas Ilias Tagkopoulos Predicting the evolution of Escherichia coli by a data-driven approach
description	How reproducible evolutionary processes are remains an important question in evolutionary biology. Here, the authors compile a compendium of more than 15,000 mutation events for Escherichia coli under 178 distinct environmental settings, and develop an ensemble of predictors to predict evolution at a gene level.
format	article
author	Xiaokang Wang Violeta Zorraquino Minseung Kim Athanasios Tsoukalas Ilias Tagkopoulos
author_facet	Xiaokang Wang Violeta Zorraquino Minseung Kim Athanasios Tsoukalas Ilias Tagkopoulos
author_sort	Xiaokang Wang
title	Predicting the evolution of Escherichia coli by a data-driven approach
title_short	Predicting the evolution of Escherichia coli by a data-driven approach
title_full	Predicting the evolution of Escherichia coli by a data-driven approach
title_fullStr	Predicting the evolution of Escherichia coli by a data-driven approach
title_full_unstemmed	Predicting the evolution of Escherichia coli by a data-driven approach
title_sort	predicting the evolution of escherichia coli by a data-driven approach
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/3d716d97abf6460ea0ada536a16d3e36
work_keys_str_mv	AT xiaokangwang predictingtheevolutionofescherichiacolibyadatadrivenapproach AT violetazorraquino predictingtheevolutionofescherichiacolibyadatadrivenapproach AT minseungkim predictingtheevolutionofescherichiacolibyadatadrivenapproach AT athanasiostsoukalas predictingtheevolutionofescherichiacolibyadatadrivenapproach AT iliastagkopoulos predictingtheevolutionofescherichiacolibyadatadrivenapproach
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Predicting the evolution of Escherichia coli by a data-driven approach

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