DocumentCode :
3194209
Title :
Mining protein complexes based on connected affinity clique extension
Author :
Peng Li ; Xiaohua Hu ; Tingting He ; Junmin Zhao ; Ming Zhang ; Xianjun Shen
Author_Institution :
Sch. of Comput., Central China Normal Univ., Wuhan, China
fYear :
2013
fDate :
18-21 Dec. 2013
Firstpage :
53
Lastpage :
56
Abstract :
A novel algorithm based on Connected Affinity Clique Extension (CACE) for mining overlapping functional modules in protein interaction network is proposed in this paper. In this approach, the value of protein connected affinity is interpreted as the reliability and possibility of interaction which is inferred from protein complexes. The protein interaction network is constructed as a weighted graph, and the weigh is dependent on the connected affinity coefficient. The experimental results of our CACE in two test data sets show that the CACE can detect the functional modules much more effective and accurate compared with other state-of-art algorithms CPM and IPC-MCE.
Keywords :
bioinformatics; molecular biophysics; proteins; CACE algorithm; CPM algorithm; Connected Affinity Clique Extension; IPC-MCE algorithm; connected affinity coefficient; overlapping functional modules mining; protein complexes; protein interaction network; reliability; weighted graph; Algorithm design and analysis; Bioinformatics; Clustering algorithms; Communities; Protein engineering; Proteins; Algorithm CACE; Connected affinity; Overlapping functional modules; effective and accurate;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
Type :
conf
DOI :
10.1109/BIBM.2013.6732459
Filename :
6732459
Link To Document :
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