Ontology highlight
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 persvasively 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.
SUBMITTER: Kovacs IA
PROVIDER: S-EPMC2932713 | biostudies-literature | 2010 Sep
REPOSITORIES: biostudies-literature
Kovács István A IA Palotai Robin R Szalay Máté S MS Csermely Peter P
PloS one 20100902 9
<h4>Background</h4>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.<h4>Methodology/principal findings</h4>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 commu ...[more]