An evaluation of the application of the genetic algorithm to the problem of ordering genetic loci on human chromosomes using radiation hybrid data.
We consider the problem of ordering detectable genetic loci along a chromosome by minimizing the number of obligatory breaks that can be inferred from radiation hybrid data. The problem bears some resemblance to the travelling-salesman problem, for which genetic algorithms have been used with considerable success. We find that the results from other studies on closely related problems are not directly transferable, and although we did find a genetic algorithm that performed well in this application it would appear that this algorithm is highly sensitive to any changes in the problem. Moreover, a very simple stochastic algorithm performed almost as well as our much more complicated and computer-intensive genetic algorithm and it did so in a fraction of the time. While we do not dispute that genetic algorithms can work on large complicated problems, the various modifications and fine-tuning necessary for good performance tend to be highly problem specific and they are often only arrived at after an exhaustive exploration of possibilities. Thus, we would dispute any claim that genetic algorithms are robust in their form and range of applicability.
Bansal
A
A
School of Mathematics and Statistics, University of Sheffield, UK.
Cannings
C
C
Sheehan
N
N
D000465:Algorithms; D000483:Alleles; D000818:Animals; D002874:Chromosome Mapping; D002877:Chromosomes, Human / Q000235:genetics*; D006224:Cricetinae; D005069:Evaluation Studies as Topic; D015894:Genome, Human; D006801:Humans; D006822:Hybrid Cells; D008433:Mathematics; D008957:Models, Genetic; D009154:Mutation; D011336:Probability