AbstractDetermining the sequence of genes along a region of DNA from the results of experimental data is a difficult task called Map Assembly. A map indicates the order of the genes and other markers called restriction enzymes. It is a time consuming activity, carried out manually by the geneticist. The data from which maps are produced contain a high degree of error, due to experimental limitations, and several feasible solutions may be constructed from the same data. Distinguishing between competing solutions relies on the geneticist's subjective judgement. Although computer applications have been developed for map assembly they have been either restricted in the amount of data that could be handled or they addressed related problems.
This thesis has investigated and developed suitable computer techniques for automating map assembly. A novel objective method for evaluating maps was devised that was based on the expert's heuristics. The method was successful in identifying optimal maps. A new search technique based on a form of genetic algorithm(GA) was developed to generate potential maps from a set of experimental data. The objective system for evaluating maps was incorporated into the GA. Optimal gene maps could be generated automatically, then merged together to produce a multi-gene map. In many cases, the sequence of genes and restriction enzymes was very close to the sequence as determined manually by the geneticist but could be produced in a fraction of the time.
|Date of Award||Jun 1995|
The application of artificial intelligence techniques to a sequencing problem in the biological domain
Walker, J. (Author). Jun 1995
Student thesis: Doctoral Thesis