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

  1. Lookup NU author(s)
  2. Dr Dominic Searson
  3. Professor David Leahy
  4. Dr Mark Willis
Author(s)Searson DP, Leahy DE, Willis MJ
Editor(s)Ao, S-I., Castillo, O., Huang, X.
Publication type Book Chapter
Book TitleIntelligent Control and Computer Engineering
Series TitleLecture Notes in Electrical Engineering
Full text is available for this publication:
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
Place PublishedNetherlands
ActionsLink to this publication
Library holdingsSearch Newcastle University Library for this item