Name
Abstract | ||
|---|---|---|
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. 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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1142/S0219720015500031 | JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY |
Keywords | Field | DocType |
Network alignment,conserved functional modules,graph optimization,graph theory | Protein–protein interaction,Search algorithm,Artificial intelligence,Graph theory,Pairwise comparison,Decision problem,Heuristic (computer science),Precision and recall,Algorithm,Smith–Waterman algorithm,Bioinformatics,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
13 | 2 | 0219-7200 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenbin Chen | 1 | 8 | 3.58 |
| Matthew C. Schmidt | 2 | 65 | 6.36 |
| Wenhong Tian | 3 | 158 | 27.51 |
| Nagiza F. Samatova | 4 | 861 | 74.04 |
| Shaohong Zhang | 5 | 0 | 0.34 |