An efficient algorithm for pairwise local alignment of protein interaction networks

Chen, Wenbin; Schmidt, Matthew; Tian, Wenhong; Samatova, Nagiza F.; Zhang, Shaohong

doi:10.1142/S0219720015500031

An efficient algorithm for pairwise local alignment of protein interaction networks

Journal Article · Wed Apr 01 00:00:00 EDT 2015 · Journal of Bioinformatics and Computational Biology

DOI:https://doi.org/10.1142/S0219720015500031· OSTI ID:1331086

Chen, Wenbin ^[1]; Schmidt, Matthew ^[2]; Tian, Wenhong ^[3]; Samatova, Nagiza F. ^[2]; Zhang, Shaohong ^[4]

Guangzhou Univ., Guangzhou (People's Republic of China); Fudan Univ., Shanghai (People's Republic of China); Nanjing Univ., Jiangsu (People's Republic of China)
North Carolina State Univ., Raleigh, NC (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Univ. of Electronic and Technology of China, Sichuan (People's Republic of China)
Guangzhou Univ., Guangzhou (People's Republic of China)

Recently, researchers seeking to understand, modify, and create beneficial traits in organisms have looked for evolutionarily conserved patterns of protein interactions. Their conservation likely means that the proteins of these conserved functional modules are important to the trait's expression. In this paper, we formulate the problem of identifying these conserved patterns as a graph optimization problem, and develop a fast heuristic algorithm for this problem. We compare the performance of our network alignment algorithm to that of the MaWISh algorithm [Koyuturk M, Kim Y, Topkara U, Subramaniam S, Szpankowski W, Grama A, Pairwise alignment of protein interaction networks, J Comput Biol 13(2): 182-199, 2006.], which bases its search algorithm on a related decision problem formulation. We find that our algorithm discovers conserved modules with a larger number of proteins in an order of magnitude less time. In conclusion, the protein sets found by our algorithm correspond to known conserved functional modules at comparable precision and recall rates as those produced by the MaWISh algorithm.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1331086

Journal Information:: Journal of Bioinformatics and Computational Biology, Journal Name: Journal of Bioinformatics and Computational Biology Journal Issue: 02 Vol. 13; ISSN 0219-7200

Publisher:: World ScientificCopyright Statement

Country of Publication:: United States

Language:: English

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An efficient algorithm for pairwise local alignment of protein interaction networks

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References (14)

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