Biological networks: Comparison, conservation, and evolution via relative description length

Benny Chor, Tamir Tuller*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


We describe a new approach for comparing cellular-biological networks and finding conserved regions in two or more such networks. Our distance measure is based on the description length of one network, given the description of the other one, and it is efficiently computable. We employ these distances as inputs for generating phylogenetic trees. Using KEGG's metabolic networks as our starting point, we obtained trees that are not perfect, but are very good (considering the characteristics of the inputs). Our approach enables us to identify conserved regions among more than a dozen metabolic networks, and among two protein interaction networks. These conserved regions appear to be biologically relevant, proving the viability of our approach.

Original languageEnglish
Pages (from-to)817-838
Number of pages22
JournalJournal of Computational Biology
Issue number6
StatePublished - Jul 2007


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


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