Detecting overlapping protein communities in disease networks

Abstract

In this work we propose a novel hybrid technique for overlapping community detection in biological networks able to exploit both the available quantitative and the semantic information, that we call Semantically Enriched Fuzzy C-Means Spectral Modularity (SE-FSM) community detection method. We applied SE-FSM in analyzing Protein-protein interactions (PPIs) networks of HIV-1 infection and Leukemia in Homo sapiens. SE-FSM found significant overlapping biological communities. In particular, it found a strong relationship between HIV-1 and Leukemia as their communities share several significant pathways, and biological functions.