Deterministic graph-theoretic algorithm for detecting modules in biological interaction networks

—Accumulating evidence suggests that biological systems exhibit modular organization. Accurate identification of modularity is vital for understanding this organization. A recent approach, Modules of Networks (MoNet), introduced an intuitive module definition and a clear detection method based on a ranked list of edges generated by the Girvan-Newman (G-N) algorithm. The resulting modules from a yeast network showed significant association with known biological processes, indicative of the method’s utility. Despite MoNet’s usefulness, systematic bias in the method leads to varied results across trials. MoNet modules also exclude some network regions. Such deficiencies limit meaningful analysis of a network. To address these shortcomings, we have developed a deterministic G-N algorithm (dG-N) and a new agglomerative algorithm, Deterministic Modularization of Networks (dMoNet). dMoNet simultaneously processes structurally equivalent edges while preserving the intuitive foundatio...

• Type: Journal
• Year: 2010
• Where: IJBRA
• Authors: Roger L. Chang, Feng Luo, Stuart Johnson, Richard H. Scheuermann
• Keywords: Algorithm, IJBRA 2010, Interaction Networks, Monet