An approach for determining evolutionary distance in network-based phylogenetic analysis

Tingting Zhou, Chun Chung Chan, Yi Pan, Zhenghua Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Network-based phylogenetic analysis explores phylogenetic relationships among different organisms by comparing their biological networks, especially metabolic networks. The differences between networks, often expressed as evolutionary distances, are normally measured using the plain Jaccard distance. In this paper, we show enzymes are different in phylogenetic conservation and topological importance, which are correlated significantly. Inspired by this observation, we propose a new approach to determine evolutionary distances. Our approach considers not only the number of different enzymes in different organisms, but also the phylogenetic or topological difference of individual enzymes. The resulting evolutionary distance measures are compared with the plain Jaccard distance by use of 16s rRNA-based distance as reference. It shows that new distance measures make errors smaller in all test cases of comparison.
Original languageEnglish
Title of host publicationBioinformatics Research and Applications - Fourth International Symposium, ISBRA 2008, Proceedings
Pages38-49
Number of pages12
DOIs
Publication statusPublished - 27 Aug 2008
Event4th International Symposium on Bioinformatics Research and Applications, ISBRA 2008 - Atlanta, GA, United States
Duration: 6 May 20089 May 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4983 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Symposium on Bioinformatics Research and Applications, ISBRA 2008
CountryUnited States
CityAtlanta, GA
Period6/05/089/05/08

Keywords

  • Evolutionary distance
  • Jaccard distance
  • Metabolic network comparison
  • Network-based phylogenetic analysis
  • Phylogenetic conservation
  • Topological importance

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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