Bloat Free Genetic Programming: Application to Human Oral Bioavailability Prediction



Being able to predict the human oral bioavailability for a potential new drug is extremely important for the drug discovery process. This problem has been addressed by several prediction tools, with Genetic Programming providing some of the best results ever achieved. In this paper we use the newest developments of Genetic Programming, in particular the latest bloat control method, Operator Equalisation, to find out how much improvement we can achieve on this problem. We show examples of some actual solutions and discuss their quality, comparing them with previously published results. We identify some unexpected behaviors related to overfitting, and discuss the way for further improving the practical usage of the Genetic Programming approach.


Genetic Programming, Bloat, Code Growth, Operator Equalisation, Drug Discovery, Human Oral Bioavailability, Prediction, Symbolic Regression, Overfitting, Solution Length, Feature Selection


Genetic Programming

Related Project

EnviGP - Improving Genetic Programming for the Environment and Other Applications


International Journal of Data Mining and Bioinformatics, Vol. 6, #6, pp. 585-601, Inderscience, November 2012

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