The Evolution of Stochastic Regular Motifs for Protein Sequences

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@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

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