ProRank: A method for detecting protein complexes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Citations (Scopus)

Abstract

Detecting protein complexes from protein-protein interaction (PPI) network is becoming a difficult challenge in computational biology. Observations show that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. This paper introduces a novel method for detecting protein-complexes from PPI by using a protein ranking algorithm (ProRank) and incorporating an evolutionary relationships between proteins in the network. The method successfully predicted 57 out of 81 benchmarked protein complexes created from the Munich Information Center for Protein Sequence (MIPS). The level of the accuracy achieved using ProRank in comparison to other recent methods for detecting protein complexes is a strong argument in favor of our proposed method. Datasets, programs and results are available at http://faculty.uaeu.ac.ae/nzaki/ProRank.htm.

Original languageEnglish
Title of host publicationGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation
Pages209-216
Number of pages8
DOIs
Publication statusPublished - Aug 13 2012
Event14th International Conference on Genetic and Evolutionary Computation, GECCO'12 - Philadelphia, PA, United States
Duration: Jul 7 2012Jul 11 2012

Publication series

NameGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation

Other

Other14th International Conference on Genetic and Evolutionary Computation, GECCO'12
Country/TerritoryUnited States
CityPhiladelphia, PA
Period7/7/127/11/12

Keywords

  • pageRank algorithm
  • pair-wise similarity
  • protein complex detection
  • protein-protein interaction

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

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