Genetic Programming in Data Mining for Drug Discovery

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

@InCollection{langdon:2004:ECDM,
  author =       "W. B. Langdon and S. J. Barrett",
  title =        "Genetic Programming in Data Mining for Drug
                 Discovery",
  booktitle =    "Evolutionary Computing in Data Mining",
  publisher =    "Springer",
  year =         "2004",
  editor =       "Ashish Ghosh and Lakhmi C. Jain",
  volume =       "163",
  series =       "Studies in Fuzziness and Soft Computing",
  chapter =      "10",
  pages =        "211--235",
  keywords =     "genetic algorithms, genetic programming, drug
                 discovery, ROC fitness, ADMET",
  ISBN =         "3-540-22370-3",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/wbl_bioavail.pdf",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/wbl_bioavail.ps.gz",
  URL =          "http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-175-22-33980376-0,00.html",
  abstract =     "Genetic programming (GP) is used to extract from rat
                 oral bioavailability (OB) measurements simple,
                 interpretable and predictive QSAR models which both
                 generalise to rats and to marketed drugs in humans.
                 Receiver Operating Characteristics (ROC) curves for the
                 binary classifier produced by machine learning show no
                 statistical difference between rats (albeit without
                 known clearance differences) and man. Thus evolutionary
                 computing offers the prospect of in silico ADME
                 screening e.g. for virtual chemicals, for
                 pharmaceutical drug discovery.",
  notes =        "wbl_bioavail postscript and PDF page numbering and
                 figures NOT identical to published book",
  size =         "25 pages",
}

Genetic Programming entries for William B Langdon S J Barrett

Citations