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FUNN-MG: A Metagenomic Systems Biology Computational Framework

  • Leandro Corrêa
  • Ronnie Alves
  • Fabiana Goés
  • Cristian Chaparro
  • Lucinéia Thom
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8826)

Abstract

Microorganisms abound everywhere. Though we know they play key roles in several ecosystems, too little is known about how these complex communities work. To act as a community they must interact with each other in order to achieve such community stability in which proper functions allows the microbial community to adapt in complex environment conditions. Thus, to effectively understand microbial genetic networks one needs to explore them by means of a systems biology approach. The proposed approach extends the metagenomic gene-centric view by taking into account the set of genes present in a metagenome and also the complex links of interactions among these genes and by treating the microbiome as a single biological system. In this paper, we present the FUNN-MG computational framework to explore functional modules in microbial genetic networks.

Keywords

systems biology gene and pathway enrichment analysis graph representation graph visualization metagenomics 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Leandro Corrêa
    • 1
  • Ronnie Alves
    • 1
    • 2
    • 4
  • Fabiana Goés
    • 1
  • Cristian Chaparro
    • 1
  • Lucinéia Thom
    • 3
  1. 1.PPGCCUniversidade Federal do ParáBelémBrazil
  2. 2.Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier, UMR 5506Université Montpellier 2, Centre National de la Recherche ScientifiqueMontpellierFrance
  3. 3.PPGCUniversidade Federal do Rio Grande do SulPorto AlegreBrazil
  4. 4.Institut de Biologie ComputationnelleMontpellierFrance

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