The Evolution of Stochastic Regular Motifs for Protein Sequences

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{ross:2002:ngc,
  author =       "Brian J. Ross",
  title =        "The Evolution of Stochastic Regular Motifs for Protein
                 Sequences",
  journal =      "New Generation Computing",
  year =         "2002",
  volume =       "20",
  number =       "2",
  pages =        "187--213",
  month =        feb,
  keywords =     "genetic algorithms, genetic programming, protein,
                 motif, stochastic regular expressions, Protein Motifs,
                 Stochastic Regular Expressions, Grammatical Genetic
                 Programming, Evolutionary Computation",
  URL =          "http://www.ohmsha.co.jp/ngc/ngc2002.htm",
  URL =          "http://www.cosc.brocku.ca/~bross/research/sredna_ngc.pdf",
  URL =          "http://citeseer.ist.psu.edu/507503.html",
  abstract =     "Stochastic regular motifs are evolved for protein
                 sequences using genetic programming. The motif
                 language, SRE-DNA, is a stochastic regular expression
                 language suitable for denoting biosequences. Three
                 restricted versions of SRE-DNA are used as target
                 languages for evolved motifs. The genetic programming
                 experiments are implemented in DCTG-GP, which is a
                 genetic programming system that uses logic--based
                 attribute grammars to define the target language for
                 evolved programs. Earlier preliminary work tested
                 SRE-DNA's viability as a representation language for
                 aligned protein sequences. This work establishes that
                 SRE-DNA is also suitable for evolving motifs for
                 unaligned sets of sequences.",
}

Genetic Programming entries for Brian J Ross

Citations