Abstract
We study different genetic algorithm operators for one permutation problem associated with the Human Genome Project—the assembly of DNA sequence fragments from a parent clone whose sequence is unknown into a consensus sequence corresponding to the parent sequence. The sorted-order representation, which does not require specialized operators, is compared with a more traditional permutation representation, which does require specialized operators. The two representations and their associated operators are compared on problems ranging from 2K to 34K base pairs (KB). Edge-recombination crossover used in conjunction with several specialized operators is found to perform best in these experiments; these operators solved a 10KB sequence, consisting of 177 fragments, with no manual intervention. Natural building blocks in the problem are exploited at progressively higher levels through “macro-operators.” This significantly improves performance.
Original language | English (US) |
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Pages (from-to) | 11-33 |
Number of pages | 23 |
Journal | Machine Learning |
Volume | 21 |
Issue number | 1 |
DOIs | |
State | Published - Oct 1995 |
Externally published | Yes |
Keywords
- DNA fragment assembly
- building blocks
- edge-recombination crossover
- genetic algorithms
- human genome project
- ordering problems
ASJC Scopus subject areas
- Software
- Artificial Intelligence