Genetic algorithm for applying constraints in chromosome classification

Abstract A genetic algorithm was used to solve the optimization problem of jointly classifying human chromosomes subject to constraints imposed by the context of a metaphase cell. When applying the constraint of no more than two chromosomes per class to two widely used data sets, error rates as low as in the previously best-known classification method were obtained, confirming that a genetic algorithm is indeed a suitable tool for investigating this problem. Applying a further constraint based on the presumed close similarity of the banding pattern of homologous chromosome pairs resulted in only a small improvement in error rates, but did assist in the discrimination of chromosomes that should be rejected.

[1]  P A Errington,et al.  Application of artificial neural networks to chromosome classification. , 1993, Cytometry.

[2]  Jim Piper.  Classification of chromosomes constrained by expected class size , 1986, Pattern Recognit. Lett..

[3]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[4]  Arnold W. M. Smeulders,et al.  Human chromosome classification based on local band descriptors , 1989, Pattern Recognit. Lett..

[5]  Peter Kleinschmidt,et al.  A hybrid method for automatic chromosome karyotyping , 1994, Pattern Recognit. Lett..

[6]  F. Arrighi,et al.  Automated homologue matching of human G-banded chromosomes. , 1986, Computers in biology and medicine.

[7]  Jim Graham,et al.  An efficient transportation algorithm for automatic chromosome karyotyping , 1991, Pattern Recognit. Lett..

[8]  J. Piper,et al.  On fully automatic feature measurement for banded chromosome classification. , 1989, Cytometry.

[9]  W. P. Sweeney,et al.  Classification of chromosomes using a probabilistic neural network. , 1994, Cytometry.

[10]  J. Piper,et al.  Computer-aided classification of human chromosomes: a review , 1994 .

[11]  Jim Piper,et al.  Improved chromosome classification using monotonic functions of mahalanobis distance and the transportation method , 1994, Math. Methods Oper. Res..

[12]  E Granum,et al.  Automatically inferred Markov network models for classification of chromosomal band pattern structures. , 1990, Cytometry.

[13]  John J. Grefenstette,et al.  Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.