Connectedness of PPI network neighborhoods identifies regulatory hub proteins

Bioinformatics. 2011 Apr 15;27(8):1135-42. doi: 10.1093/bioinformatics/btr099. Epub 2011 Mar 2.

Abstract

Motivation: With the growing availability of high-throughput protein-protein interaction (PPI) data, it has become possible to consider how a protein's local or global network characteristics predict its function.

Results: We introduce a graph-theoretic approach that identifies key regulatory proteins in an organism by analyzing proteins' local PPI network structure. We apply the method to the yeast genome and describe several properties of the resulting set of regulatory hubs. Finally, we demonstrate how the identified hubs and putative target gene sets can be used to identify causative, functional regulators of differential gene expression linked to human disease.

Availability: Code is available at http://bcb.cs.tufts.edu/hubcomps.

Contact: fox.andrew.d@gmail.com; slonim@cs.tufts.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Anti-Bacterial Agents / pharmacology
  • Disease / genetics
  • Drug Resistance, Fungal
  • Gene Expression Profiling
  • Gentamicins / pharmacology
  • Humans
  • Models, Statistical
  • Protein Interaction Mapping / methods*
  • Saccharomyces cerevisiae Proteins / genetics
  • Saccharomyces cerevisiae Proteins / metabolism
  • Yeasts / drug effects
  • Yeasts / genetics
  • Yeasts / metabolism

Substances

  • Anti-Bacterial Agents
  • Gentamicins
  • Saccharomyces cerevisiae Proteins