Protein complex prediction via dense subgraphs and false positive analysis.

ABSTRACT: Many proteins work together with others in groups called complexes in order to achieve a specific function. Discovering protein complexes is important for understanding biological processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI networks), which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some approaches are topology-based, where highly connected proteins are predicted to be complexes; some propose different clustering algorithms using partitioning, overlaps among clusters for networks modeled with unweighted or weighted graphs; and others use density of clusters

SUBMITTER: Hernandez C 

PROVIDER: S-EPMC5609739 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature