Genetic Programming in Data Mining for Drug Discovery

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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