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Generating protein interaction maps from incomplete data: application to fold assignment.

M Lappe1, J Park, O Niggemann

  • 1Structural Genomics Group, The European Bioinformatics Institute, EMBL Outstation, Cambridge CB10 1SD, UK. lappe@ebi.ac.uk

Bioinformatics (Oxford, England)
|July 27, 2001
PubMed
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We developed a framework to map protein-protein interactions using graph theory. This method integrates fragmented data and predicts protein structures, advancing our understanding of cellular networks.

Area of Science:

  • Systems Biology
  • Bioinformatics
  • Network Science

Background:

  • Cellular function is understood as complex interaction networks.
  • Protein-protein interaction (PPI) data is often fragmented and incomplete.
  • Modeling PPIs as graphs provides a framework for analysis.

Purpose of the Study:

  • To develop a framework for generating comprehensive overviews of protein-protein interactions.
  • To create interaction maps of cellular networks from fragmented data.
  • To derive network representations that simplify complexity while preserving essential architecture.

Main Methods:

  • Representing protein-protein interaction data as undirected graphs.
  • Contracting graphs based on hierarchical classifications to create induced interactions.

Related Experiment Videos

  • Integrating and comparing interaction data from diverse sources and organisms at various abstraction levels.

    • Main Results:

    • Applied the framework to analyze the DIP compendium and yeast two-hybrid data.
    • Observed a scale-free network architecture that persists across abstraction levels.
    • Developed a network-context algorithm for protein fold assignment with 30% accuracy, independent of sequence similarity.

    Conclusions:

    • The framework enables the integration and analysis of large-scale, heterogeneous PPI data.
    • Network abstraction reveals persistent scale-free properties and facilitates downward projection of interactions.
    • The protein fold prediction algorithm offers a novel approach for structural assignment of uncharacterized proteins.