Biological networks; comparison, conservation, and evolutionary trees (extended abstract)

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Abstract

We describe a new approach for comparing cellular-biological networks, and finding conserved regions in two or more such networks. We use the length of describing one network, given the description of the other one, as a distance measure. We employ these distances as inputs for generating phylogenetic trees. Our algorithms are fast enough for generating phylogenetic tree of more than two hundreds metabolic networks that appear in KEGG. Using KEGG's metabolic networks as our starting point, we got trees that are not perfect, but are surprisingly good. We also found conserved regions among more than a dozen metabolic networks, and among two protein interaction networks. These conserved regions seem biologically relevant, proving the viability of our approach.

Original languageEnglish
Title of host publicationResearch in Computational Molecular Biology - 10th Annual International Conference, RECOMB 2006, Proceedings
Pages30-44
Number of pages15
DOIs
StatePublished - 2006
Event10th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2006 - Venice, Italy
Duration: 2 Apr 20065 Apr 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3909 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2006
Country/TerritoryItaly
CityVenice
Period2/04/065/04/06

Keywords

  • Biological networks
  • Compression
  • Conserved regions
  • Metabolic networks
  • Network evolution
  • Networks' comparison
  • Relative description length
  • Tree reconstruction

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