COMNA: Core-attachment based protein complex detection via multiple network alignment

Protein complexes are important functional units for performing biological functions and revealing cellular organization principles, and its detection is a fundamental problem in computational biology. In this paper, we present a novel algorithm COMNA by using orthology relationship across different species to complement the complex detection of a single protein-protein interaction (PPI) network, which can identify protein complexes from multiple PPI networks simultaneously. First, we propose a novel measure, high-order edge closure coefficient, to assess the reliability of interactions and then identify core-attachment based complexes from each PPI network. Second, we cooperate with the orthology information from multiple PPI network alignment to mine more complementary complexes. Finally, we merge the highly overlapping complexes by constructing an overlapping graph. We compare COMNA with eight state-of-the-art protein complex identification algorithms on three datasets, and the experimental results show that COMNA can detect complexes from PPI networks with higher accuracy.