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Background: Network communities help the functional organization andevolution of complex networks. However, the development of a method, which isboth fast and accurate, provides modular overlaps and partitions of aheterogeneous network, has proven to be rather difficult. Methodology/PrincipalFindings: Here we introduce the novel concept of ModuLand, an integrativemethod family determining overlapping network modules as hills of an influencefunction-based, centrality-type community landscape, and including severalwidely used modularization methods as special cases. As various adaptations ofthe method family, we developed several algorithms, which provide an efficientanalysis of weighted and directed networks, and (1) determine pervasivelyoverlapping modules with high resolution; (2) uncover a detailed hierarchicalnetwork structure allowing an efficient, zoom-in analysis of large networks;(3) allow the determination of key network nodes and (4) help to predictnetwork dynamics. Conclusions/Significance: The concept opens a wide range ofpossibilities to develop new approaches and applications including networkrouting, classification, comparison and prediction.

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