POINT: A database for the prediction of protein-protein interactions based on the orthologous interactome

Tao Wei Huang, An Chi Tien, Wen Shien Huang, Yuan Chii G. Lee, Chin Lin Peng, Huei Hun Tseng, Cheng Yan Kao, Chi Ying F. Huang

Research output: Contribution to journalArticlepeer-review

94 Citations (Scopus)

Abstract

Summary: One possible path towards understanding the biological function of a target protein is through the discovery of how it interfaces within protein-protein interaction networks. The goal of this study was to create a virtual protein-protein interaction model using the concepts of orthologous conservation (or interologs) to elucidate the interacting networks of a particular target protein. POINT (the prediction of interactome database) is a functional database for the prediction of the human protein-protein interactome based on available orthologous interactome datasets. POINT integrates several publicly accessible databases, with emphasis placed on the extraction of a large quantity of mouse, fruit fly, worm and yeast protein-protein interactions datasets from the Database of Interacting Proteins (DIP), followed by conversion of them into a predicted human interactome. In addition, protein-protein interactions require both temporal synchronicity and precise spatial proximity. POINT therefore also incorporates correlated mRNA expression clusters obtained from cell cycle microarray databases and subcellular localization from Gene Ontology to further pinpoint the likelihood of biological relevance of each predicted interacting sets of protein partners.

Original languageEnglish
Pages (from-to)3273-3276
Number of pages4
JournalBioinformatics
Volume20
Issue number17
DOIs
Publication statusPublished - Nov 22 2004

ASJC Scopus subject areas

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

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