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2005 Technical Reports

Finding Molecular Complexes through Multiple Layer Clustering of Protein Interaction Networks

Bill Andreopoulos, Aijun An, Xiangji Huang and Xiaogang Wang

Technical Report CS-2005-13

York University

October 2005


Motivation: One of the purposes of studying and analyzing protein-protein interaction networks (PINs) is to identify new protein complexes that guide the workings of a cell. Clustering algorithms for PIN data presented in the literature often do not consider the layered structure of protein complexes, creating instead a flat clustering.

Results: We propose the MULIC clustering algorithm that produces layered clusters of PIN data. We applied MULIC clustering to five PINs, including three yeast PINs. MULIC clusters correlate with known protein complexes in the MIPS database. For example, a large cluster of 79 proteins significantly overlaps with a known complex of 88 proteins.

Conclusions: MULIC clustering can assist in predicting protein complexes. Given the layered structure of the MULIC clusters, the proteins in top layers tend to be more representative of protein complexes than proteins in bottom layers. Lab experiments on finding an unknown complex or determining the potential effects of a drug can initially be guided by proteins in top layers and later move to bottom layers of clusters.

Keywords: Clustering, multiple layer, protein interaction network, complex.

Notice:The work presented in the paper above is covered by pending patents and copyright. Publication of this paper does not grant rights to any intellectual property. All rights reserved.

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