Bioinformatics Advance Access published online on April 27, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm156
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Alignment of molecular networks by integer quadratic programming


aBeijing Wuzi University, Beijing 101149, China bAcademy of Mathematics and Systems Science,CAS, Beijing 100080, China cOsaka Sangyo University, Osaka 574-8530, Japan
corresponding author. Xiang-Sun Zhang, E-mail: zxs{at}amt.ac.cn, Luonan Chen, chen{at}elec.osaka-sandai.ac.jp
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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 paper, 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.
*these authors contributed equally
Associate Editor: Prof. John Quackenbush
Received on December 20, 2006; revised on March 19, 2007; accepted on April 17, 2007
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