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Portuguese Conference on Artificial Intelligence

EPIA 2009: Progress in Artificial Intelligence pp 65–76Cite as

Using Operator Equalisation for Prediction of Drug Toxicity with Genetic Programming

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5816))

Abstract

Predicting the toxicity of new potential drugs is a fundamental step in the drug design process. Recent contributions have shown that, even though Genetic Programming is a promising method for this task, the problem of predicting the toxicity of molecular compounds is complex and difficult to solve. In particular, when executed for predicting drug toxicity, Genetic Programming undergoes the well-known phenomenon of bloat, i.e. the growth in code size during the evolutionary process without a corresponding improvement in fitness. We hypothesize that this might cause overfitting and thus prevent the method from discovering simpler and potentially more general solutions. For this reason, in this paper we investigate two recently defined variants of the operator equalization bloat control method for Genetic Programming. We show that these two methods are bloat free also when executed on this complex problem. Nevertheless, overfitting still remains an issue. Thus, contradicting the generalized idea that bloat and overfitting are strongly related, we argue that the two phenomena are independent from each other and that eliminating bloat does not necessarily eliminate overfitting.

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Author information

Authors and Affiliations

  1. Dipartimento di Informatica, Sistemistica e Comunicazione (D.I.S.Co.), University of Milano-Bicocca, Milan, Italy

    Leonardo Vanneschi

  2. CISUC, Department of Informatics Engineering, University of Coimbra, Polo II, Coimbra, Portugal

    Sara Silva

Authors
  1. Leonardo Vanneschi
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  2. Sara Silva
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Editor information

Editors and Affiliations

  1. IEETA/Department of Electronics & Telecommunication, University of Aveiro, Campus Santiago, P.O. Box, 3810-153, Aveiro, Portugal

    Luís Seabra Lopes

  2. LSE-IEETA/DETI, Universidade de Aveiro, Portugal

    Nuno Lau

  3. Universidade de Aveiro, Aveiro, Portugal

    Pedro Mariano

  4. School of Informatics, Indiana University, Bloomington, IN, USA, and Computational Biology Collaboratorium, Instituto ulbenkian da Ciencia, Portugal

    Luís M. Rocha

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© 2009 Springer-Verlag Berlin Heidelberg

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Vanneschi, L., Silva, S. (2009). Using Operator Equalisation for Prediction of Drug Toxicity with Genetic Programming. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds) Progress in Artificial Intelligence. EPIA 2009. Lecture Notes in Computer Science(), vol 5816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04686-5_6

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  • DOI: https://doi.org/10.1007/978-3-642-04686-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04685-8

  • Online ISBN: 978-3-642-04686-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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