Langdon, W.B.;
Barrett, S.J.;
(2004)
Genetic programming in data mining for drug discovery.
In: Ghosh, A. and Jain, L.C., (eds.)
Evolutionary Computing in Data Mining.
(pp. 211-235).
Springer-Verlag Berlin and Heidelberg GmbH & Co. K: Germany.
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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 classier produced by machine learning show no statistical dierence between rats (albeit without known clearance dierences) and man. Thus evolutionary computing oers the prospect of in silico ADME screening, e.g. for \virtual" chemicals, for pharmaceutical drug discovery.
| Type: | Book chapter |
|---|---|
| Title: | Genetic programming in data mining for drug discovery |
| ISBN: | 3540223703 |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | This Eprint appeared as Chapter 10 in Evolutionary Computing in Data Mining, A. Ghosh and L.C. Jain, eds. |
| URI: | https://discovery.ucl.ac.uk/id/eprint/572 |
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