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Book Sections Year : 2019

The Methodology Behind Network Thinking: Graphs to Analyze Microbial Complexity and Evolution

Abstract

In the post genomic era, large and complex molecular datasets from genome and metagenome sequencing projects expand the limits of what is possible for bioinformatic analyses. Network-based methods are increasingly used to complement phylogenetic analysis in studies in molecular evolution, including comparative genomics, classification, and ecological studies. Using network methods, the vertical and horizontal relationships between all genes or genomes, whether they are from cellular chromosomes or mobile genetic elements, can be explored in a single expandable graph. In recent years, development of new methods for the construction and analysis of networks has helped to broaden the availability of these approaches from programmers to a diversity of users. This chapter introduces the different kinds of networks based on sequence similarity that are already available to tackle a wide range of biological questions, including sequence similarity networks, gene-sharing networks and bipartite graphs, and a guide for their construction and analyses.
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hal-02324786 , version 1 (07-04-2021)

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Attribution - CC BY 4.0

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Andrew B. Watson, Romain Lannes, Jananan S Pathmanathan, Raphaël Méheust, Slim Karkar, et al.. The Methodology Behind Network Thinking: Graphs to Analyze Microbial Complexity and Evolution. Evolutionary Genomics, pp.271-308, 2019, ⟨10.1007/978-1-4939-9074-0_9⟩. ⟨hal-02324786⟩
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