Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes.

ABSTRACT: Most protein complex detection methods utilize unsupervised techniques to cluster densely connected nodes in a protein-protein interaction (PPI) network, in spite of the fact that many true complexes are not dense subgraphs. Supervised methods have been proposed recently, but they do not answer why a group of proteins are predicted as a complex, and they have not investigated how to detect new complexes of one species by training the model on the PPI data of another species. We propose a novel supervised method to address these issues. The key idea is to discover emerging patterns (EPs), a type of contrast pattern, which can clearly distinguish true complexes from random subgraphs in a PPI network. An integrative score of EPs is defined to measure how likely a subgraph of proteins can form

SUBMITTER: Liu Q 

PROVIDER: S-EPMC4751475 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature