Optimizing a global alignment of protein interaction networks.

Bioinformatics

Computer Science and Artificial Intelligence Laboratory and Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA, Department of Computer Science and Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 30013, Taiwan.

Published: November 2013

Motivation: The global alignment of protein interaction networks is a widely studied problem. It is an important first step in understanding the relationship between the proteins in different species and identifying functional orthologs. Furthermore, it can provide useful insights into the species' evolution.

Results: We propose a novel algorithm, PISwap, for optimizing global pairwise alignments of protein interaction networks, based on a local optimization heuristic that has previously demonstrated its effectiveness for a variety of other intractable problems. PISwap can begin with different types of network alignment approaches and then iteratively adjust the initial alignments by incorporating network topology information, trading it off for sequence information. In practice, our algorithm efficiently refines other well-studied alignment techniques with almost no additional time cost. We also show the robustness of the algorithm to noise in protein interaction data. In addition, the flexible nature of this algorithm makes it suitable for different applications of network alignment. This algorithm can yield interesting insights into the evolutionary dynamics of related species.

Availability: Our software is freely available for non-commercial purposes from our Web site, http://piswap.csail.mit.edu/.

Contact: bab@csail.mit.edu or csliao@ie.nthu.edu.tw.

Supplementary Information: Supplementary data are available at Bioinformatics online.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3799479PMC
http://dx.doi.org/10.1093/bioinformatics/btt486DOI Listing

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