Genetic Algorithms, Operators, and DNA Fragment Assembly

Rebecca J. Parsons, Stephanie Forrest, Christian Burks

Research output: Contribution to journalArticlepeer-review

86 Scopus citations

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 languageEnglish (US)
Pages (from-to)11-33
Number of pages23
JournalMachine Learning
Volume21
Issue number1
DOIs
StatePublished - Oct 1995
Externally publishedYes

Keywords

  • DNA fragment assembly
  • building blocks
  • edge-recombination crossover
  • genetic algorithms
  • human genome project
  • ordering problems

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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