An efficient algorithm for pairwise local alignment of protein interaction networks
- 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.
- Research Organization:
- Oak Ridge National Lab. (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, Vol. 13, Issue 02; ISSN 0219-7200
- Publisher:
- World ScientificCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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