• Medientyp: E-Artikel
  • Titel: EDEN: evolutionary dynamics within environments
  • Beteiligte: Münch, Philipp C; Stecher, Bärbel; McHardy, Alice C
  • Erschienen: Oxford University Press (OUP), 2017
  • Erschienen in: Bioinformatics
  • Sprache: Englisch
  • DOI: 10.1093/bioinformatics/btx394
  • ISSN: 1367-4803; 1367-4811
  • Schlagwörter: Computational Mathematics ; Computational Theory and Mathematics ; Computer Science Applications ; Molecular Biology ; Biochemistry ; Statistics and Probability
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  • Beschreibung: <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Summary</jats:title> <jats:p>Metagenomics revolutionized the field of microbial ecology, giving access to Gb-sized datasets of microbial communities under natural conditions. This enables fine-grained analyses of the functions of community members, studies of their association with phenotypes and environments, as well as of their microevolution and adaptation to changing environmental conditions. However, phylogenetic methods for studying adaptation and evolutionary dynamics are not able to cope with big data. EDEN is the first software for the rapid detection of protein families and regions under positive selection, as well as their associated biological processes, from meta- and pangenome data. It provides an interactive result visualization for detailed comparative analyses.</jats:p> </jats:sec> <jats:sec> <jats:title>Availability and implementation</jats:title> <jats:p>EDEN is available as a Docker installation under the GPL 3.0 license, allowing its use on common operating systems, at http://www.github.com/hzi-bifo/eden.</jats:p> </jats:sec> <jats:sec> <jats:title>Contact</jats:title> <jats:p>alice.mchardy@helmholtz-hzi.de</jats:p> </jats:sec> <jats:sec> <jats:title>Supplementary information</jats:title> <jats:p>Supplementary data are available at Bioinformatics online.</jats:p> </jats:sec>
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