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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

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Published on: August 14, 2018

Detecting network communities: an application to phylogenetic analysis.

Roberto F S Andrade1, Ivan C Rocha-Neto, Leonardo B L Santos

  • 1Institute of Physics, Federal University of Bahia, Campus Universitário de Ondina, Salvador, Bahia, Brazil.

Plos Computational Biology
|May 17, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel network-based method for identifying communities in weighted networks, successfully applied to phylogenetic analysis of protein sequences to reveal evolutionary relationships.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Network Science

Background:

  • Protein similarity networks can reveal phylogenetically useful information.
  • Analyzing network modularity is key to understanding evolutionary relationships.
  • Existing methods may not fully capture complex network structures.

Purpose of the Study:

  • To develop and apply a new network-based method for community identification in weighted complex networks.
  • To utilize this method for phylogenetic analysis using protein sequence similarity.
  • To demonstrate the retrieval of sound biological information from network properties.

Main Methods:

  • Construction of protein similarity networks where weights represent similarity indexes.
  • Application of the Newman-Girvan algorithm and neighborhood matrix for community detection.
  • Analysis of network topology changes to identify distinct modules.

Main Results:

  • The network-based method successfully identified modules corresponding to bacterial phyla and classes.
  • High internal consistency was observed, with an 84% match rate in community pertinence comparisons.
  • The method demonstrated reliability comparable to Bayesian, distance, likelihood, and parsimony methods.

Conclusions:

  • The proposed network-based method is a powerful tool for extracting modularity information from weighted networks.
  • This approach is effective for phylogenetic analysis, offering insights into evolutionary relationships.
  • The method retrieves biological information without requiring additional biological assumptions beyond BLAST.