Detection of Complexes in Biological Networks Through Diversified Dense Subgraph Mining.

ABSTRACT: Protein-protein interaction (PPI) networks, providing a comprehensive landscape of protein interaction patterns, enable us to explore biological processes and cellular components at multiple resolutions. For a biological process, a number of proteins need to work together to perform a job. Proteins densely interact with each other, forming large molecular machines or cellular building blocks. Identification of such densely interconnected clusters or protein complexes from PPI networks enables us to obtain a better understanding of the hierarchy and organization of biological processes and cellular components. However, most existing graph clustering algorithms on PPI networks often cannot effectively detect densely connected subgraphs and overlapped subgraphs. In this article, we formulate

SUBMITTER: Ma X 

PROVIDER: S-EPMC5610454 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature