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