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Predicting the Toxicity of Chemical Compounds Using GPTIPS: A Free Genetic Programming Toolbox for MATLAB

  • Dominic P. SearsonEmail author
  • David E. Leahy
  • Mark J. Willis
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 70)

Abstract

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 http://sites.google.com/site/gptips4matlab/.

Keywords

Genetic programming Symbolic regression QSAR Toxicity 

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Dominic P. Searson
    • 1
    Email author
  • David E. Leahy
    • 2
  • Mark J. Willis
    • 3
  1. 1.Northern Institute for Cancer ResearchNewcastle UniversityNewcastle upon TyneUK
  2. 2.School of Chemical Engineering and Advanced MaterialsNewcastle UniversityNewcastle upon TyneUK
  3. 3.School of Chemical Engineering and Advanced MaterialsNewcastle UniversityNewcastle upon TyneUK

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