Community landscapes: An integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics

István A. Kovács, Robin Palotai, Máté S. Szalay, Peter Csermely*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

145 Scopus citations

Abstract

Background: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

Original languageEnglish (US)
Article numbere12528
Pages (from-to)1-14
Number of pages14
JournalPloS one
Volume5
Issue number9
DOIs
StatePublished - 2010

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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