Alignment of molecular networks by integer quadratic programming.
BACKGROUND
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.


BACKGROUND
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.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Zhenping
Li
L
Beijing Wuzi University, Beijing 101149, China.
Zhang
Shihua
S
Wang
Yong
Y
Zhang
Xiang-Sun
XS
Chen
Luonan
L
D000465:Algorithms; D003198:Computer Simulation; D015870:Gene Expression / Q000502:physiology*; D020869:Gene Expression Profiling / Q000379:methods*; D008954:Models, Biological; D011382:Programming, Linear; D020543:Proteome / Q000235:genetics* / Q000378:metabolism*; D016415:Sequence Alignment / Q000379:methods*; D015398:Signal Transduction / Q000502:physiology*
D020543:Proteome