Part of Faraday data fusion project.
In high through put screening minute quantities of chemicals are placed mechanically in a tiny holes (known as wells) on a tray. Trays typically have at least 96 wells (sometimes many more). Activity between the chemicals is indicated by set in it up to produce a chemical dye which fluorescence. The amount of reaction between the chemicals is measured by measuring the brightness of the well after shining light upon to it. NB the whole process is heavily automated, allowing many different chemicals to be studied simultaneously.
Instead we extend and combine existing data mining techniques to the P450 problem. Many classifiers are trained on HTS data. They are then fused using genetic programming to yield a composite predictor.
Graph (purple) shows size fair crossover and the 4 mutation operators have succeeded in controlling bloat.
The evolved classifier and how it used is described here.
W.B.Langdon@cs.ucl.ac.uk 30 August 2001 (last update 4 Oct 2012).