Automated learning of a detector for the cores of /spl alpha/-helices in protein sequences via genetic programming

摘要

The author used J.R. Koza's (1992) genetic programming to evolve programs that classified contiguous regions of proteins as being /spl alpha/-helix cores or not. He snipped positive and negative examples of /spl alpha/-helix core regions out of a set of 90 proteins. These proteins were chosen from the Brookhaven Protein Data Bank to be non-homologous. The fitness of the programs was defined as the correlation coefficient between the observed and the predicted /spl alpha/-helicity of the above regions. The fittest program produced by the genetic programming system that predicted the training set at least as well as the testing set had a correlation of 0.4818 between the observed classifications and the classifications predicted by the program (on the proteins in the testing set).