IOPTICS-GSO for identifying protein complexes from dynamic PPI networks.

ABSTRACT: BACKGROUND:Identifying protein complexes plays an important role for understanding cellular organization and functional mechanisms. As plenty of evidences have indicated that dense sub-networks in dynamic protein-protein interaction network (DPIN) usually correspond to protein complexes, identifying protein complexes is formulated as density-based clustering. METHODS:In this paper, a new approach named iOPTICS-GSO is developed, which is the improved Ordering Points to Identify the Clustering Structure (OPTICS) algorithm with Glowworm swarm optimization algorithm (GSO) to optimize the parameters in OPTICS when finding dense sub-networks. In our iOPTICS-GSO, the concept of core node is redefined and the Euclidean distance in OPTICS is replaced with the improved similarity between the nodes i

SUBMITTER: Lei X 

PROVIDER: S-EPMC5751787 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature