Abstract
Identifying protein complexes from protein-protein interact ion (PPI) networks is an important issue in proteomics and bioinformatics. And various computational methods have been developed to solve it. In this paper, an approach called Hierarchical Link Clustering and Core-Attachment (HLC-CA) was proposed to detect protein complexes by integrating an HLC algorithm and the immanent core-attachment structure in protein complexes. Compared with other methods, HLC-CA has a low time complexity and few parameters to tune. HLC-CA includes four steps. Firstly, an HLC algorithm was used to obtain candidate clusters. Secondly, a density threshold was employed to filter the clusters in ord e r to identify complex cores. Thirdly, each core was recruited attachments by introducing the closeness. Finally, the cores chosen in the second step and their corresponding attachments were used to compose protein complexes. Evaluation results show that the proposed HLC-CA method outperforms most of the state-of-the-art methods.
Keywords: Complex networks, core-attachment structure, hierarchical link clustering, overlapping communities, protein complexes, protein-protein interactions.