Genetic Map Construction with Constraints

Dominic A. Clark, Christopher J. Rawlings, and Sylvie Doursenot

A pilot program, CME, is described for generating a physical genetic map from hybridization fingerprinting data. CME is implemented in the parallel constraint logic programming language ElipSys. The features of constraint logic programming are used to enable the integration of preexisting mapping information (partial probe orders from cytogenetic maps and local physical maps) into the global map generation process, while parallelism enables the search space to be traversed more efficiently. CME was tested using data from chromosome 2 of Schizosaccharomyces pombe and was found able to generate maps as well as (and sometimes better than) a more traditional method. This paper illustrates the practical benefits of using a symbolic logic programming language and shows that the features of constraint handling and parallel execution bring the development of practical systems based on AI programming technologies nearer to being a reality.

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