Name
Abstract | ||
|---|---|---|
This paper proposes a hybrid genetic algorithm for multiple sequence alignment. The algorithm evolves guide sequences and aligns input sequences based on the guide sequences. It also embeds a local search heuristic to search the problem space effectively. In the experiments for various data sets, the proposed algorithm showed the performance comparable to existing algorithms. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1145/1143997.1144051 | GECCO |
Keywords | Field | DocType |
hybrid genetic search,problem space,multiple sequence alignment,various data set,algorithm evolves guide sequence,aligns input,hybrid genetic algorithm,local search heuristic,guide sequence,proposed algorithm,genetic algorithm,genetic algorithms,genetics,local search,bioinformatics | Sequence alignment,Heuristic,Alignment-free sequence analysis,Computer science,Artificial intelligence,Local search (optimization),Cultural algorithm,Multiple sequence alignment,Population-based incremental learning,Machine learning,Genetic algorithm | Conference |
ISBN | Citations | PageRank |
1-59593-186-4 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seung-Hyun Moon | 1 | 3 | 0.86 |
| Sung-Soon Choi | 2 | 112 | 11.03 |
| Byung-Ro Moon | 3 | 844 | 58.71 |