DocumentCode :
67310
Title :
Survey: Functional Module Detection from Protein-Protein Interaction Networks
Author :
Junzhong Ji ; Aidong Zhang ; Chunnian Liu ; Xiaomei Quan ; Zhijun Liu
Author_Institution :
Beijing Univ. of Technol., Beijing, China
Volume :
26
Issue :
2
fYear :
2014
fDate :
Feb. 2014
Firstpage :
261
Lastpage :
277
Abstract :
A protein-protein interaction (PPI) network is a biomolecule relationship network that plays an important role in biological activities. Studies of functional modules in a PPI network contribute greatly to the understanding of biological mechanism. With the development of life science and computing science, a great amount of PPI data has been acquired by various experimental and computational approaches, which presents a significant challenge of detecting functional modules in a PPI network. To address this challenge, many functional module detecting methods have been developed. In this survey, we first analyze the existing problems in detecting functional modules and discuss the countermeasures in the data preprocess and postprocess. Second, we introduce some special metrics for distance or graph developed in clustering process of proteins. Third, we give a classification system of functional module detecting methods and describe some existing detection methods in each category. Fourth, we list databases in common use and conduct performance comparisons of several typical algorithms by popular measurements. Finally, we present the prospects and references for researchers engaged in analyzing PPI networks.
Keywords :
biology computing; pattern classification; pattern clustering; proteins; PPI network; biological activity; biological mechanism; biomolecule relationship network; classification system; computing science; data postprocessing; data preprocessing; functional module detection method; life science; protein clustering process; protein-protein interaction networks; Bioinformatics; Clustering algorithms; Educational institutions; IEEE Computer Society; Measurement; Proteins; Protein-protein interaction network; clustering algorithm; computation approach; functional module detection;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2012.225
Filename :
6353426
Link To Document :
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