PC2P: parameter-free network-based prediction of protein complexes.

ABSTRACT:

Motivation

Prediction of protein complexes from protein-protein interaction (PPI) networks is an important problem in systems biology, as they control different cellular functions. The existing solutions employ algorithms for network community detection that identify dense subgraphs in PPI networks. However, gold standards in yeast and human indicate that protein complexes can also induce sparse subgraphs, introducing further challenges in protein complex prediction.

Results

To address this issue, we formalize protein complexes as biclique spanned subgraphs, which include both sparse and dense subgraphs. We then cast the problem of protein complex prediction as a network partitioning into biclique spanned subgraphs with removal of minimum number of edges, called coherent par

SUBMITTER: Omranian S 

PROVIDER: S-EPMC8034538 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature