High functional coherence in k-partite protein cliques of protein interaction networks

Liu, Qian, Chen, Yi-Ping Phoebe and Li, Jinyan 2009, High functional coherence in k-partite protein cliques of protein interaction networks, in BIBM 2009 : Proccedings of the 2009 IEEE International Conference on Bioinformatics and Biomedicine, IEEE Computer Society, Piscataway, N. J., pp. 111-117.

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Title High functional coherence in k-partite protein cliques of protein interaction networks
Formatted title High functional coherence in k-Partite protein cliques of protein interaction networks
Author(s) Liu, Qian
Chen, Yi-Ping Phoebe
Li, Jinyan
Conference name IEEE International Conference on Bioinformatics and Biomedicine (2009 : Washingston, D. C.)
Conference location Washington, D.C., USA
Conference dates 1–4 November 2009
Title of proceedings BIBM 2009 : Proccedings of the 2009 IEEE International Conference on Bioinformatics and Biomedicine
Editor(s) [Unknown]
Publication date 2009
Conference series International Conference on Bioinformatics and Biomedicine
Start page 111
End page 117
Publisher IEEE Computer Society
Place of publication Piscataway, N. J.
Keyword(s) Keywords-k-Partite Protein Cliques
K-partite Graphs
Protein
Functional Coherence
Summary We introduce a new topological concept called k-partite protein cliques to study protein interaction (PPI) networks. In particular, we examine functional coherence of proteins in k-partite protein cliques. A k-partite protein clique is a k-partite maximal clique comprising two or more nonoverlapping protein subsets between any two of which full interactions are exhibited. In the detection of PPI’s k-partite maximal cliques, we propose to transform PPI networks into induced K-partite graphs with proteins as vertices where edges only exist among the graph’s partites. Then, we present a k-partite maximal clique mining (MaCMik) algorithm to enumerate k-partite maximal cliques from K-partite graphs. Our MaCMik algorithm is applied to a yeast PPI network. We observe that there does exist interesting and unusually high functional coherence in k-partite protein cliques—most proteins in k-partite protein cliques, especially those in the same partites, share the same functions. Therefore, the idea of k-partite protein cliques suggests a novel approach to characterizing PPI networks, and may help function prediction for unknown proteins.
ISBN 9780769538853
Language eng
Field of Research 080301 Bioinformatics Software
Socio Economic Objective 890299 Computer Software and Services not elsewhere classified
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
HERDC collection year 2009
Persistent URL http://hdl.handle.net/10536/DRO/DU:30028577

Document type: Conference Paper
Collection: School of Information Technology
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