Community Detection in Large-Scale Bipartite Biological Networks.

ABSTRACT: Networks are useful tools to represent and analyze interactions on a large, or genome-wide scale and have therefore been widely used in biology. Many biological networks-such as those that represent regulatory interactions, drug-gene, or gene-disease associations-are of a bipartite nature, meaning they consist of two different types of nodes, with connections only forming between the different node sets. Analysis of such networks requires methodologies that are specifically designed to handle their bipartite nature. Community structure detection is a method used to identify clusters of nodes in a network. This approach is especially helpful in large-scale biological network analysis, as it can find structure in networks that often resemble a "hairball" of interactions in visualizations. Of

SUBMITTER: Calderer G 

PROVIDER: S-EPMC8099108 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature