Toggle Main Menu Toggle Search

Open Access padlockePrints

Predicting the toxicity of chemical compounds using GPTIPS: a free genetic programming toolbox for MATLAB

Lookup NU author(s): Dr Dominic Searson, Professor David Leahy, Dr Mark Willis



In this contribution GPTIPS, a free, open source MATLAB toolbox for performing symbolic regression by genetic programming (GP) is introduced. GPTIPS is specifically designed to evolve mathematical models of predictor response data that are “multigene” in nature, i.e. linear combinations of low order non-linear transformations of the input variables. The functionality of GPTIPS is demonstrated by using it to generate an accurate, compact QSAR (quantitative structure activity relationship) model of existing toxicity data in order to predict the toxicity of chemical compounds. It is shown that the low-order “multigene” GP methods implemented by GPTIPS can provide a useful alternative, as well as a complementary approach, to currently accepted empirical modelling and data analysis techniques. GPTIPS and documentation is available for download at

Publication metadata

Author(s): Searson DP, Leahy DE, Willis MJ

Editor(s): Ao, S-I., Castillo, O., Huang, X.

Publication type: Book Chapter

Publication status: Published

Book Title: Intelligent Control and Computer Engineering

Year: 2011

Volume: 70

Pages: 83-93

Series Title: Lecture Notes in Electrical Engineering

Publisher: Springer

Place Published: Netherlands


DOI: 10.1007/978-94-007-0286-8_8

Library holdings: Search Newcastle University Library for this item

ISBN: 9789400702868