Detection of Protein Complexes Using Hierarchical Link Clustering and Core-Attachment Structure§
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.
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