Automatic Learning of a Detector for alpha-helices in Protein Sequences Via Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{icga93:handley,

• author = "Simon Handley",
• title = "Automatic Learning of a Detector for alpha-helices in Protein Sequences Via Genetic Programming",
• year = "1993",
• booktitle = "Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-93",
• editor = "Stephanie Forrest",
• publisher = "Morgan Kaufmann",
• address = "University of Illinois at Urbana-Champaign",
• month = "17-21 " # jul,
• keywords = "genetic algorithms, genetic programming",
• pages = "271--278",
• size = "8 pages",
• abstract = "This paper reports preliminary results from an attempt to predict the secondary structure of globular proteins. The genetic programming system was used to evolve programs that classified each residue in ten proteins as being either in an a-helix or in a {"}coil{"} (everything else). The proteins were chosen to be non-homologous and to contain mostly a-helices. The ten proteins were divided in half into a training set, that was used to drive the evolution, and a testing set, that was used to test the resultant programs. The fitness of the programs was based on the correlation coefficient between the observed and the predicted a-helicity of the residues. The fittest program produced by the genetic programming system had a correlation of 0.316 between the observed classifications and the classifications predicted by the program (on the proteins in the testing set).",
• broken = "http://www-leland.stanford.edu/~shandley/postscript/alpha-helices.ps.gz",
• notes = "GP based upon balkiness and hydrophilicity of the 7 amino acid residues closest to a point along the chain (repeat for whole chain). Train on five known P test on five more. NOT GOOD, GP learns structure of the training set well but this is not a very good predictor for the others",

}

Genetic Programming entries for Simon G Handley

Citations