DocumentCode :
680168
Title :
An integrated approach to identify protein complex based on best neighbor and modularity increment
Author :
Xianjun Shen ; Yanli Zhao ; Yanan Li ; Jincai Yang ; Tingting He ; Xiaohua Hu
Author_Institution :
Sch. of Comput., Central China Normal Univ., Wuhan, China
fYear :
2013
fDate :
18-21 Dec. 2013
Firstpage :
57
Lastpage :
60
Abstract :
In order to overcome the limitations of global modularity and the deficiency of local modularity, we introduce a hybrid modularity measure LGQ (Local-Global Quantification) which adopts a suitable modularity adjustable parameter to control the balance of global detecting capability and local search capability in Protein-Protein Interaction (PPI) network. On the other hand, a new protein complex mining algorithm called BN-LGQ has been proposed, which integrates the definitions of best neighbor node and the modularity increment. And by comparison with other known algorithms, the experimental results show BN-LGQ performs a better accuracy on predicting protein complexes and has a higher match with the reference protein complexes. Moreover, it can identify protein complexes with better biological significance in PPI network.
Keywords :
biochemistry; bioinformatics; data mining; feature extraction; molecular biophysics; molecular configurations; proteins; BN-LGQ; LGQ method; PPI network; best neighbor node definition; biologically significant protein complex identification; global detecting capability; global modularity limitations; hybrid modularity measure; integrated approach; local modularity deficiency; local search capability; local-global quantification method; modularity adjustable parameter; modularity increment definition; protein complex mining algorithm; protein complex prediction accuracy; protein-protein interaction network; reference protein complex match; Accuracy; Clustering algorithms; Prediction algorithms; Protein engineering; Proteins; Semantics; Protein-Protein Interaction network; best neighbor node; modularity increment; protein complexes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
Type :
conf
DOI :
10.1109/BIBM.2013.6732460
Filename :
6732460
Link To Document :
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