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Related Experiment Videos

Online predicted human interaction database.

Kevin R Brown1, Igor Jurisica

  • 1Division of Cancer Informatics, Ontario Cancer Institute, University of Toronto, Canada.

Bioinformatics (Oxford, England)
|January 20, 2005
PubMed
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The Online Predicted Human Interaction Database (OPHID) provides a comprehensive resource of predicted human protein-protein interactions (PPIs). It integrates data from multiple species and databases, aiding in the study of complex human biological networks.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput experiments are crucial for mapping protein-protein interaction (PPI) networks.
  • Complexities in higher eukaryotes like humans have hindered experimental PPI network elucidation.
  • Existing databases often lack comprehensive coverage for human PPIs.

Purpose of the Study:

  • To develop a comprehensive web-based database of predicted human protein-protein interactions (PPIs).
  • To provide a valuable resource for researchers studying human biological networks.
  • To facilitate the systematic elucidation of human PPIs.

Main Methods:

  • Integrated literature-derived human PPI data from BIND, HPRD, and MINT.
  • Incorporated cross-species PPI predictions from yeast, C. elegans, D. melanogaster, and M. musculus.

Related Experiment Videos

  • Evaluated predicted interactions using protein domains, gene co-expression, and Gene Ontology (GO) terms.

    • Main Results:

    • The Online Predicted Human Interaction Database (OPHID) was established, containing 23,889 predicted human PPIs.
    • OPHID offers query functionality for single or multiple protein IDs.
    • Results can be visualized using a custom graph visualization program.

    Conclusions:

    • OPHID serves as a valuable, publicly accessible resource for human PPI data.
    • The database aids in understanding complex human biological networks through predicted interactions.
    • It supports further research in human molecular biology and disease.