Evolutionary computation method for pattern recognition of cis-acting sites

Created by W.Langdon from gp-bibliography.bib Revision:1.3788

@Article{Howard:2003:CIB,
  author =       "Daniel Howard and Karl Benson",
  title =        "Evolutionary computation method for pattern
                 recognition of cis-acting sites",
  journal =      "Biosystems",
  year =         "2003",
  volume =       "72",
  number =       "1-2",
  pages =        "19--27",
  month =        nov,
  note =         "Special Issue on Computational Intelligence in
                 Bioinformatics",
  keywords =     "genetic algorithms, genetic programming, Finite State
                 Automata, DNA, human genome, promoter, evolutionary
                 computation, bioinformatics",
  ISSN =         "0303-2647",
  doi =          "doi:10.1016/S0303-2647(03)00132-1",
  URL =          "http://www.sciencedirect.com/science/article/B6T2K-49NRT53-1/2/a695c769043ab9105da3bb6cf90fe774",
  URL =          "http://www.ncbi.nlm.nih.gov/PubMed/",
  abstract =     "This paper develops an evolutionary method that learns
                 inductively to recognize the makeup and the position of
                 very short consensus sequences, cis-acting sites, which
                 are a typical feature of promoters in genomes. The
                 method combines a Finite State Automata (FSA) and
                 Genetic Programming (GP) to discover candidate promoter
                 sequences in primary sequence data. An experiment
                 measures the success of the method for promoter
                 prediction in the human genome. This class of method
                 can take large base pair jumps and this may enable it
                 to process very long genomic sequences to discover gene
                 specific cis-acting sites, and genes which are
                 regulated together.",
}

Genetic Programming entries for Daniel Howard Karl A Benson

Citations