An algorithm for modularity analysis of directed and weighted biological networks based on edge-betweenness centrality | Zendy

Jeongah Yoon | Zendy; Anselm Blumer | Zendy; Kyongbum Lee | Zendy

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An algorithm for modularity analysis of directed and weighted biological networks based on edge-betweenness centrality

Author(s) -

Jeongah Yoon,

Anselm Blumer,

Kyongbum Lee

Publication year - 2006

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btl533

Subject(s) - betweenness centrality , modularity (biology) , centrality , computer science , network analysis , enhanced data rates for gsm evolution , complex network , function (biology) , biological network , algorithm , theoretical computer science , data mining , artificial intelligence , computational biology , mathematics , biology , physics , evolutionary biology , world wide web , genetics , combinatorics , quantum mechanics

Modularity analysis is a powerful tool for studying the design of biological networks, offering potential clues for relating the biochemical function(s) of a network with the 'wiring' of its components. Relatively little work has been done to examine whether the modularity of a network depends on the physiological perturbations that influence its biochemical state. Here, we present a novel modularity analysis algorithm based on edge-betweenness centrality, which facilitates the use of directional information and measurable biochemical data.

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