Evolving Turing machines for Biosequences Recognition and Analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Edgar E. Vallejo and Fernando Ramos",
  title =        "Evolving {Turing} machines for Biosequences
                 Recognition and Analysis",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2001",
  year =         "2001",
  editor =       "Julian F. Miller and Marco Tomassini and 
                 Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and 
                 William B. Langdon",
  volume =       "2038",
  series =       "LNCS",
  pages =        "192--203",
  address =      "Lake Como, Italy",
  publisher_address = "Berlin",
  month =        "18-20 " # apr,
  organisation = "EvoNET",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming,
                 Bioinformatics, DNA, Turing machines, Multiple Sequence
  ISBN =         "3-540-41899-7",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=192",
  size =         "12 pages",
  abstract =     "This article presents a genetic programming system for
                 biosequence recognition and analysis. In our model, a
                 population of Turing machines evolves the capability of
                 biosequence recognition using genetic algorithms. We
                 use HIV sequences as the working example. Experimental
                 results indicate that evolved Turing machines are
                 capable of recognizing HIV sequences in a collection of
                 training sets. In addition, we demonstrate that the
                 evolved Turing machines can be used to approximate the
                 multiple sequence alignment problem.",
  notes =        "EuroGP'2001, part of \cite{miller:2001:gp}",

Genetic Programming entries for Edgar E Vallejo Fernando Ramos Quintana