Deterministic graph-theoretic algorithm for detecting modules in biological interaction networks.
|Title||Deterministic graph-theoretic algorithm for detecting modules in biological interaction networks.|
|Publication Type||Journal Article|
|Year of Publication||2010|
|Authors||Chang RL, Luo F, Johnson S, Scheuermann RH|
|Journal||Int J Bioinform Res Appl|
|Keywords||Algorithms, Protein Interaction Mapping, Proteome, Proteomics|
An approach for module identification, Modules of Networks (MoNet), introduced an intuitive module definition and clear detection method using edges ranked by the Girvan-Newman algorithm. Modules from a yeast network showed significant association with biological processes, indicating the method's utility; however, systematic bias leads to varied results across trials. MoNet modules also exclude some network regions. To address these shortcomings, we developed a deterministic version of the Girvan-Newman algorithm and a new agglomerative algorithm, Deterministic Modularization of Networks (dMoNet). dMoNet simultaneously processes structurally equivalent edges while preserving intuitive foundations of the MoNet algorithm and generates modules with full network coverage.
|Alternate Title||Int J Bioinform Res Appl|