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Bioinformatics Advance Access originally published online on April 27, 2007
Bioinformatics 2007 23(13):1631-1639; doi:10.1093/bioinformatics/btm156
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Alignment of molecular networks by integer quadratic programming

Zhenping Li 1,2,*, Shihua Zhang 2,3,*, Yong Wang 2,5, Xiang-Sun Zhang 3,{dagger} and Luonan Chen 4,5,6,7,{dagger}

1Beijing Wuzi University, Beijing 101149, China, 2Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China, 3Graduate University of Chinese Academy of Sciences, Beijing 100049, China, 4Institute of Systems Biology, Shanghai University, Shanghai 200444, China, 5Osaka Sangyo University, Osaka 574-8530, Japan, 6ERATO Aihara Complexity Modelling Project, JST, Tokyo 153-8530, Japan and 7Institite of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan

{dagger}To whom correspondence should be addressed.


   Abstract

Motivation: With more and more data on molecular networks (e.g. protein interaction networks, gene regulatory networks and metabolic networks) available, the discovery of conserved patterns or signaling pathways by comparing various kinds of networks among different species or within a species becomes an increasingly important problem. However, most of the conventional approaches either restrict comparative analysis to special structures, such as pathways, or adopt heuristic algorithms due to computational burden.

Results: In this article, to find the conserved substructures, we develop an efficient algorithm for aligning molecular networks based on both molecule similarity and architecture similarity, by using integer quadratic programming (IQP). Such an IQP can be relaxed into the corresponding quadratic programming (QP) which almost always ensures an integer solution, thereby making molecular network alignment tractable without any approximation. The proposed framework is very flexible and can be applied to many kinds of molecular networks including weighted and unweighted, directed and undirected networks with or without loops.

Availability: Matlab code and data are available from http://zhangroup.aporc.org/bioinfo/MNAligner or http://intelligent.eic.osaka-sandai.ac.jp/chenen/software/MNAligner, or upon request from authors.

Contact: zxs{at}amt.ac.cn, chen{at}eic.osaka-sandai.ac.jp

Supplementary information: Supplementary data are available at Bioinformatics online.

*The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

Associate Editor: John Quackenbush


Received on December 20, 2006; revised on March 19, 2007; accepted on April 17, 2007

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