Module identification in bipartite and directed networks.

Module identification in bipartite and directed networks. Research Abstract Details 

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Module identification in bipartite and directed networks. Abstract Text:

Roger ,Marta Sales-Pardo, Amaral,Roger ,Marta Sales-Pardo, Amaral,

Modularity is one of the most prominent properties of real-world complex networks. Here, we address the issue of module identification in two important classes of networks: bipartite networks and directed unipartite networks. Nodes in bipartite networks are divided into two nonoverlapping sets, and the links must have one end node from each set. Directed unipartite networks only have one type of node, but links have an origin and an end. We show that directed unipartite networks can be conveniently represented as bipartite networks for module identification purposes. We report on an approach especially suited for module detection in bipartite networks, and we define a set of random networks that enable us to validate the approach.

Module identification in bipartite and directed networks. Publishing Authors By Initials

R ,M Sales-Pardo,LA Amaral,R ,M Sales-Pardo,LA Amaral,

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Module identification in bipartite and directed networks. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: Physical review. E, Statistical, nonlinear, and so

VOLUME: 76

Page Numbers: 036102

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ISSN: 1539-3755

DAY: 6

MONTH: 09

YEAR: 2007

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LANGUAGE: eng

NlmUniqueID: 101136452

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Grant and Affiliation Information for Module identification in bipartite and directed networks.

AFFILIATION: Northwestern Institute on Complex Systems (NICO) and Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, USA.

Country: United States

AGENCY: United States NIGMS

GRANT: K25 GM069546-04

ACRONYM: GM

MEDLINETA: Phys Rev E Stat Nonlin Soft Ma

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