Optimizing a global alignment of protein interaction networks
File(s)Bioinformatics(2013).pdf (322.54 KB)
Published version
Author(s)
Chindelevitch, Leonid
Ma, Cheng-Yu
Liao, Chung-Shou
Berger, Bonnie
Type
Journal Article
Abstract
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.
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.
Date Issued
2013-11
Date Acceptance
2013-08-15
Citation
Bioinformatics, 2013, 29 (21), pp.2765-2773
ISSN
1367-4803
Publisher
Oxford University Press (OUP)
Start Page
2765
End Page
2773
Journal / Book Title
Bioinformatics
Volume
29
Issue
21
Copyright Statement
© The Author 2013. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://academic.oup.com/bioinformatics/article/29/21/2765/196342
Subjects
Bioinformatics
01 Mathematical Sciences
06 Biological Sciences
08 Information and Computing Sciences
Publication Status
Published
Date Publish Online
2013-09-17