articleBioinformaticsJul 29, 2004BRONZE OA

Modeling interactome: scale-free or geometric?

University of Toronto · University Health Network · +1 more institution

PubMed
Indexed incrossrefdoajpubmed

Abstract

Results

One example of large and complex networks involves protein-protein interaction (PPI) networks. We analyze PPI networks of yeast Saccharomyces cerevisiae and fruitfly Drosophila melanogaster using a newly introduced measure of local network structure as well as the standardly used measures of global network structure. We examine the fit of four different network models, including Erdos-Renyi, scale-free and geometric random network models, to these PPI networks with respect to the measures of local and global network structure. We demonstrate that the currently accepted scale-free model of PPI networks fails to fit the data in several respects and show that a random geometric model provides a much more accurate model of the PPI data. We hypothesize that only the noise in these networks is scale-free.

Conclusions

We systematically evaluate how well-different network models fit the PPI networks. We show that the structure of PPI networks is better modeled by a geometric random graph than by a scale-free model. SUPPLEMENTARY INFORMATION: Supplementary information is available at http://www.cs.utoronto.ca/~juris/data/data/ppiGRG04/

Citation impact

712
total citations
FWCI
5.79
Percentile
100%
References
58
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Interactome
  • Geometric networks
  • Random graph
  • Network model
  • Scale (ratio)
  • Complex network
  • Scale-free network
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Funding