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Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution

The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based...

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Detalles Bibliográficos
Autores principales: Corel, Eduardo, Lopez, Philippe, Méheust, Raphaël, Bapteste, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Trends Journals 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766943/
https://www.ncbi.nlm.nih.gov/pubmed/26774999
http://dx.doi.org/10.1016/j.tim.2015.12.003
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author Corel, Eduardo
Lopez, Philippe
Méheust, Raphaël
Bapteste, Eric
author_facet Corel, Eduardo
Lopez, Philippe
Méheust, Raphaël
Bapteste, Eric
author_sort Corel, Eduardo
collection PubMed
description The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families–genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts.
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spelling pubmed-47669432016-03-01 Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution Corel, Eduardo Lopez, Philippe Méheust, Raphaël Bapteste, Eric Trends Microbiol Review The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families–genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts. Elsevier Trends Journals 2016-03 /pmc/articles/PMC4766943/ /pubmed/26774999 http://dx.doi.org/10.1016/j.tim.2015.12.003 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Corel, Eduardo
Lopez, Philippe
Méheust, Raphaël
Bapteste, Eric
Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution
title Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution
title_full Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution
title_fullStr Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution
title_full_unstemmed Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution
title_short Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution
title_sort network-thinking: graphs to analyze microbial complexity and evolution
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766943/
https://www.ncbi.nlm.nih.gov/pubmed/26774999
http://dx.doi.org/10.1016/j.tim.2015.12.003
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