Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06) (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.5
Shihua Zhang , Chinese Academy of Sciences, Beijing 100080, China
Hong-Wei Liu , Renmin University of China, Beijing 100872, China
Xue-Mei Ning , Graduate University of Chinese Academy of Sciences, Beijing 100049, China
Xiang-Sun Zhang , Chinese Academy of Sciences, Beijing 100080, China
With ever increasing amount of available data on protein-protein interaction (PPI) networks, understanding the topology of the networks and then biochemical processes in cells has become a key problem. Modular architecture which encompasses groups of genes/proteins involved in elementary biological functional units is a basic form of the organization of interacting proteins. Here we propose a method that combines the line graph transformation and clique percolation clustering algorithm to detect network modules which may overlap each other in large sparse protein-protein interaction (PPI) networks. The resulting modules by the present method show a high coverage among yeast, fly, and worm PPI networks respectively. Our analysis of the yeast PPI network suggests that most of these modules have well biological significance in context of protein localization, function annotation, and protein complexes.
H. Liu, S. Zhang, X. Ning and X. Zhang, "A Graph-Theoretic Method for Mining Functional Modules in Large Sparse Protein Interaction Networks," Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)(ICDMW), Hong Kong, China, 2006, pp. 130-135.