Topological and functional comparison of community detection algorithms in biological networks.

ABSTRACT:

Background

Community detection algorithms are fundamental tools to uncover important features in networks. There are several studies focused on social networks but only a few deal with biological networks. Directly or indirectly, most of the methods maximize modularity, a measure of the density of links within communities as compared to links between communities.

Results

Here we analyze six different community detection algorithms, namely, Combo, Conclude, Fast Greedy, Leading Eigen, Louvain and Spinglass, on two important biological networks to find their communities and evaluate the results in terms of topological and functional features through Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology term enrichment analysis. At a high level, the main assessment

SUBMITTER: Rahiminejad S 

PROVIDER: S-EPMC6487005 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature