Biclique communities

Sune Lehmann, Martin Schwartz, and Lars Kai Hansen
Phys. Rev. E 78, 016108 – Published 21 July 2008

Abstract

We present a method for detecting communities in bipartite networks. Based on an extension of the k-clique community detection algorithm, we demonstrate how modular structure in bipartite networks presents itself as overlapping bicliques. If bipartite information is available, the biclique community detection algorithm retains all of the advantages of the k-clique algorithm, but avoids discarding important structural information when performing a one-mode projection of the network. Further, the biclique community detection algorithm provides a level of flexibility by incorporating independent clique thresholds for each of the nonoverlapping node sets in the bipartite network.

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  • Received 26 October 2007

DOI:https://doi.org/10.1103/PhysRevE.78.016108

©2008 American Physical Society

Authors & Affiliations

Sune Lehmann1,2,3, Martin Schwartz3,4, and Lars Kai Hansen3

  • 1Center for Complex Network Research and Department of Physics, Northeastern University, Boston, Massachusetts 02115, USA
  • 2Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard University, Boston, Massachusetts 02115, USA
  • 3Informatics and Mathematical Modelling, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
  • 4IT University of Copenhagen, DK-2300 Copenhagen S, Denmark

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Issue

Vol. 78, Iss. 1 — July 2008

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