Genetic Algorithms, Operators, and DNA Fragment Assembly
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.
Cite
Text
Parsons et al. "Genetic Algorithms, Operators, and DNA Fragment Assembly." Machine Learning, 1995. doi:10.1007/BF00993377Markdown
[Parsons et al. "Genetic Algorithms, Operators, and DNA Fragment Assembly." Machine Learning, 1995.](https://mlanthology.org/mlj/1995/parsons1995mlj-genetic/) doi:10.1007/BF00993377BibTeX
@article{parsons1995mlj-genetic,
title = {{Genetic Algorithms, Operators, and DNA Fragment Assembly}},
author = {Parsons, Rebecca J. and Forrest, Stephanie and Burks, Christian},
journal = {Machine Learning},
year = {1995},
pages = {11-33},
doi = {10.1007/BF00993377},
volume = {21},
url = {https://mlanthology.org/mlj/1995/parsons1995mlj-genetic/}
}