Protein complex discovery from protein interaction network with high false-positive rate

  • Authors:

  • Yunku Yeu;Jaegyoon Ahn;Youngmi Yoon;Sanghyun Park

  • Affiliations:

  • Dept. of Computer Science, Yonsei University, Shinchon-dong, Seodaemun-gu Seoul, Korea;Dept. of Computer Science, Yonsei University, Shinchon-dong, Seodaemun-gu Seoul, Korea;Division of Information Technology, Gachon university of Medicine & Science, Yonsu-dong, Yonsu-gu, Incheon, Korea;Dept. of Computer Science, Yonsei University, Shinchon-dong, Seodaemun-gu Seoul, Korea

  • Venue:
  • EvoBIO'11 Proceedings of the 9th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
  • Year:
  • 2011

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Abstract

Finding protein complexes and their functions is essential work for understanding biological process. However, one of the difficulties in inferring protein complexes from protein-protein interaction(PPI) network originates from the fact that protein interactions suffer from high false positive rate. We propose a complex finding algorithm which is not strongly dependent on topological traits of the protein interaction network. Our method exploits a new measure, GECSS (Gene Expression Condition Set Similarity) which considers mRNA expression data for a set of PPI. The complexes we found exhibit a higher match with reference complexes than the existing methods. Also we found several novel protein complexes, which are significantly enriched on Gene Ontology database.