A survey of computational methods for protein complex prediction from protein interaction networks

Srihari, Sriganesh and Leong, Hon Wai (2013) A survey of computational methods for protein complex prediction from protein interaction networks. Journal of Bioinformatics and Comutational Biology, 11 2: 1230002-1-1230002-27. doi:10.1142/S021972001230002X


 
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Author Srihari, Sriganesh
Leong, Hon Wai
Title A survey of computational methods for protein complex prediction from protein interaction networks
Journal name Journal of Bioinformatics and Comutational Biology   Check publisher's open access policy
ISSN 0219-7200
1757-6334
Publication date 2013-04-01
Year available 2012
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1142/S021972001230002X
Open Access Status Not yet assessed
Volume 11
Issue 2
Start page 1230002-1
End page 1230002-27
Total pages 27
Place of publication London, United Kingdom
Publisher Imperial College Press
Language eng
Subject 1303 Biochemistry
1312 Molecular Biology
1706 Computer Science Applications
Abstract Complexes of physically interacting proteins are one of the fundamental functional units responsible for driving key biological mechanisms within the cell. Their identication is therefore necessary to understand not only complex formation but also the higher level organization of the cell. With the advent of "high-throughput" techniques in molecular biology, signi¯cant amount of physical interaction data has been cataloged from organisms such as yeast, which has in turn fueled computational approaches to systematically mine complexes from the network of physical interactions among proteins (PPI network). In this survey, we review, classify and evaluate some of the key computational methods developed till date for the identi¯cation of protein complexes from PPI networks. We present two insightful taxonomies that re°ect how these methods have evolved over the years toward improving automated complex prediction. We also discuss some open challenges facing accurate reconstruction of complexes, the crucial ones being the presence of high proportion of errors and noise in current high-throughput datasets and some key aspects overlooked by current complex detection methods. We hope this review will not only help to condense the history of computational complex detection for easy reference but also provide valuable insights to drive further research in this area.
Keyword Protein complex prediction
Protein interaction network
Sparse complexes
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID R-252-000-361-112
Institutional Status Non-UQ
Additional Notes Published online 3 November 2012

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: Non HERDC
Institute for Molecular Bioscience - Publications
 
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Created: Fri, 13 Sep 2013, 21:53:39 EST by Sriganesh Srihari on behalf of Institute for Molecular Bioscience