Dense graphlet statistics of protein interaction and random networks

R. Colak, Fereydoun Hormozdiari, F. Moser, A. Schönhuth, J. Holman, M. Ester, S. C. Sahinalp

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations


Understanding evolutionary dynamics from a systemic point of view crucially depends on knowledge about how evolution affects size and structure of the organisms' functional building blocks (modules). It has been recently reported that statistics over sparse PPI graphlets can robustly monitor such evolutionary changes. However, there is abundant evidence that in PPI networks modules can be identified with highly interconnected (dense) and/or bipartite sub-graphs. We count such dense graphlets in PPI networks by employing recently developed search strategies that render related inference problems tractable. We demonstrate that corresponding counting statistics differ significantly between prokaryotes and eukaryotes as well as between "real" PPI networks and scale free network emulators. We also prove that another class of emulators, the low-dimensional geometric random graphs (GRGs) cannot contain a specific type of motifs, complete bipartite graphs, which are abundant in PPI networks.

Original languageEnglish (US)
Title of host publicationPacific Symposium on Biocomputing 2009, PSB 2009
Number of pages12
StatePublished - Dec 1 2009
Externally publishedYes
Event14th Pacific Symposium on Biocomputing, PSB 2009 - Kohala Coast, HI, United States
Duration: Jan 5 2009Jan 9 2009


Other14th Pacific Symposium on Biocomputing, PSB 2009
Country/TerritoryUnited States
CityKohala Coast, HI

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Biomedical Engineering
  • Medicine(all)


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