__MNAligner__: Alignment of molecular networks by quadratic programming

* Version 1.0
* Last update: December 18, 2006


!!!Reference

* Zhenping Li, Shi-Hua Zhang, Yong Wang, Xiang-Sun.Zhang, Luonan Chen. __[Alignment of molecular networks by integer quadratic programming|http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/13/1631]__. ''Bioinformatics'', Vol. 23, No. 13, 1631-1639, 2007. 


!!!Method

!!Motivation

With more and more data on molecular networks (e.g. protein interaction network, gene regulatory network and metabolic network) available, the discovery of conserved patterns or signal pathways by comparing various kinds of networks among different species or within a species becomes an increasingly important problem. However, due to the high complexity to compare molecular networks, most of the conventional approaches either restrict comparative analysis to special structures, such as pathways, or adopt heuristic algorithms so as to make the computation of the alignment problem tractable. 

!!Results

In this paper, to find the conserved substructures, we develop an efficient algorithm for aligning molecular networks based on both the nodes' similarity and the network 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. It can not only detect simple linear paths or tree subnets, and also uncover general subnet patterns. Meanwhile, it not only can find the simple topological substructure such as chains and trees, but also can reveal biologically meaningful units with cycles.


!!!Software

This is a beta version of the program for preliminary testing. The program is still under development.

* [MNAligner.rar|MNAligner/MNAligner.rar]

Contents:
* NetAlign.m – The main function to implement the QP model
* Two examples from the manuscript (undirected and directed):
** NetworkAlignment-eg1.m
** NetworkAlignment-eg2.m
* Generate Random Networks (undirected and directecd) from [http://www.cmth.bnl.gov/~maslov/matlab.htm]:
** GenRandomNet.m
** GenRandomDirNet.m
* Solve QP model with interior algorithm from Ye [http://www.stanford.edu/~yyye/matlab.html]
** spsolqp.m
** spphase1.m
** spphase2.m


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