This paper describes a genetic algorithm for the DNA sequencing problem. The algorithm allows the input spectrum to contain both positive and negative errors as could be expected from a hybridization experiment. The main features of the algorithm include a preprocessing step that reduces the size of the input spectrum and an efficient local optimization. In experimental tests, the algorithm performed very well against existing algorithms. The algorithm also performed very well on a large data set generated in this paper from real genomes data.
|Original language||English (US)|
|Number of pages||12|
|Journal||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Publication status||Published - Dec 1 2004|
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)