Motivation: 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.#R##N##R##N#Contact: kyongbum.lee@tufts.edu#R##N##R##N#Supplementary information: Supplementary data are available at Bioinformatics online.
['Jeongah Yoon', 'Anselm Blumer', 'Kyongbum Lee']
An algorithm for modularity analysis of directed and weighted biological networks based on edge-betweenness centrality