Extraction of knowledge on protein-protein interaction by association rule discovery

T. Oyama, K. Kitano, K. Satou, T. Ito

Research output: Contribution to journalArticlepeer-review

69 Citations (Scopus)

Abstract

Motivation: Protein-protein interactions are systematically examined using the yeast two-hybrid method. Consequently, a lot of protein-protein interaction data are currently being accumulated. Nevertheless, general information or knowledge on protein-protein interactions is poorly extracted from these data. Thus we have been trying to extract the knowledge from the protein-protein interaction data using data mining. Results: A data mining method is proposed to discover association rules related to protein-protein interactions. To evaluate the detected rules by the method, a new scoring measure of the rules is introduced. The method allowed us to detect popular interaction rules such as 'An SH3 domain binds to a proline-rich region.' These results indicate that the method may detect novel knowledge on protein-protein interactions.

Original languageEnglish
Pages (from-to)705-714
Number of pages10
JournalBioinformatics
Volume18
Issue number5
DOIs
Publication statusPublished - 2002
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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