Post Docking Filtering Using Cartesian Genetic Programming

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

@InCollection{garmendia-doval:2004:GPTP,
  author =       "A. Beatriz Garmendia-Doval and Julian Miller and 
                 S. David Morley",
  title =        "Post Docking Filtering Using Cartesian Genetic
                 Programming",
  booktitle =    "Genetic Programming Theory and Practice {II}",
  year =         "2004",
  editor =       "Una-May O'Reilly and Tina Yu and Rick L. Riolo and 
                 Bill Worzel",
  chapter =      "14",
  pages =        "225--244",
  address =      "Ann Arbor",
  month =        "13-15 " # may,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, molecular docking prediction,
                 virtual screening, machine learning, evolutionary
                 algorithms, neutral evolution",
  ISBN =         "0-387-23253-2",
  DOI =          "doi:10.1007/0-387-23254-0_14",
  abstract =     "Structure-based virtual screening is a technology
                 increasingly used in drug discovery. Although
                 successful at estimating binding modes for input
                 ligands, these technologies are less successful at
                 ranking true hits correctly by binding free energy.
                 This chapter presents the automated removal of false
                 positives from virtual hit sets, by evolving a post
                 docking filter using Cartesian Genetic
                 Programming(CGP). We also investigate characteristics
                 of CGP for this problem and confirm the absence of
                 bloat and the usefulness of neutral drift.",
  notes =        "part of \cite{oreilly:2004:GPTP2}",
}

Genetic Programming entries for A Beatriz Garmendia-Doval Julian F Miller S David Morley

Citations