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PPICPM: Identification of functional modules in PPI network by clique percolation clustering

Reference#

• Shihua Zhang, Xue-Mei Ning and Xiang-Sun Zhang. Identification of functional modules in a PPI network by clique percolation clustering. Computational Biology and Chemistry, 30(6), 445-451, 2006.

DataSet#

The protein-protein interaction (PPI) data was obtained from MIPS (http://mips.gsf.de).

• PPI_data.txt

They are functional classification catalogue scheme (Version 2.0, 18.03.2004) and protein complexes catalogue scheme (23.03.2005) respectively. So the detailed information of functional annotation and matched complexes of numerically computed modules can be seen.

• funcat-2.0_scheme
• complexcat.scheme

Results#

These files include modules' member, modules' links, and modules' information such as sizes of modules, number of modules' links and its cc-value respectively.

• NetMod_vertices.txt
• NetMod_links.txt
• NetMod_info.txt

Comparison with RNSC#

Table 1 Results of two network clustering method under the same condition.

Network	Minimum size	RNSC clusters	Our clusters
Y2k	4	48	57
Y11k	5	84	76
Y45k	7	86	119
Y78k	8	90	128

Four networks: Y2K.txt, Y11K.txt, Y45K.txt, Y78K.txt

The resulted clusters of the four network by our analysis:

• NetworkClusters.txt

The file contains functional annotation of numerical modules.

• FunctionalAnnotation.txt

The file contains all the matched pairs of numerical modules and experimental complexes cataloged in MIPS with logP < -16.

• ProteinComplex.txt

The file contains four modules' group which correspond to well-known biological pathways.

• PathwayDiscovery.txt

Figue2 shows all the pivot-like modules.

• Figure2.pdf

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