Nature Communications (Sep 2018)

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

  • Xiaokang Wang,
  • Violeta Zorraquino,
  • Minseung Kim,
  • Athanasios Tsoukalas,
  • Ilias Tagkopoulos

DOI
https://doi.org/10.1038/s41467-018-05807-z
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 12

Abstract

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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.