TopEVM: Using co-occurrence and topology patterns of enzymes in metabolic networks to construct phylogenetic trees

Tingting Zhou, Chun Chung Chan, Zhenghua Wang

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

7 Citations (Scopus)

Abstract

Network-based phylogenetic analysis typically involves representing metabolic networks as graphs and analyzing the characteristics of vertex sets using set theoretic measures. Such approaches, however, fail to take into account the structural characteristics of graphs. In this paper we propose a new pattern recognition technique, TopEVM, to help representing metabolic networks as weighted vectors. We assign weights according to co-occurrence patterns and topology patterns of enzymes, where the former are determined in a manner similar to the Tf-Idf approach used in document clustering, and the latter are determined using the degree centrality of enzymes. By comparing the weighted vectors of organisms, we determine the evolutionary distances and construct the phylogenetic trees. The resulting TopEVM trees are compared to the previous NCE trees with the NCBI Taxonomy trees as reference. It shows that TopEVM can construct trees much closer to the NCBI Taxonomy trees than the previous NCE methods.
Original languageEnglish
Title of host publication3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008
Pages225-236
Number of pages12
DOIs
Publication statusPublished - 5 Dec 2008
Event3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008 - Melbourne, VIC, Australia
Duration: 15 Oct 200817 Oct 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5265 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008
Country/TerritoryAustralia
CityMelbourne, VIC
Period15/10/0817/10/08

Keywords

  • Co-occurrence pattern
  • Degree centrality
  • Document clustering
  • Evolutionary distance
  • Metabolic network
  • Phylogenetic analysis
  • TopEVM
  • Topology pattern

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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