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Artificial Neural Networks pp 59–77Cite as

Artificial Neural Network Modeling in Environmental Toxicology

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Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 458))

Abstract

Artificial neural networks are increasingly used in environmental toxicology to find complex relationships between the ecotoxicity of xenobiotics and their structure or physicochemical properties. The raison d'être of these nonlinear tools is their ability to derive powerful QSARs for molecules presenting different mechanisms of action. In this chapter, the main QSAR models derived for aquatic and terrestrial species are reviewed. Their characteristics and modeling performances are deeply analyzed.

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  1. CTIS, 3 Chemin de la Gravière, 69140, Rillieux La Pape, France

    James Devillers

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  1. James Devillers
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Correspondence to James Devillers .

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  1. ChemQuest, Sandown, Isle of Wight, United Kingdom, PO36 8LZ, UK

    David J. Livingstone

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© 2008 Humana Press, a part of Springer Science + Business Media, LLC

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Devillers, J. (2008). Artificial Neural Network Modeling in Environmental Toxicology. In: Livingstone, D.J. (eds) Artificial Neural Networks. Methods in Molecular Biology™, vol 458. Humana Press. https://doi.org/10.1007/978-1-60327-101-1_5

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  • DOI: https://doi.org/10.1007/978-1-60327-101-1_5

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-718-1

  • Online ISBN: 978-1-60327-101-1

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