Automatic Learning of a Detector for alpha-helices in Protein Sequences Via Genetic Programming   [AL] [GP]

by

Handley, S.

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Info: Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-93 (Conference proceedings), 1993, p. 271-278
Keywords:genetic algorithms, genetic programming
Abstract:
This paper reports preliminary results from an attempt to predict the secondary structure [SS] of globular proteins. The genetic programming system [GP] 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 [GP] had a correlation of 0.316 between the observed classifications and the classifications predicted by the program (on the proteins in the testing set).
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
URL(s):(G)zipped postscript

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BibTex:
@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).",
  URL =          "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",
}