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SAR and QSAR in Environmental Research Volume 17, 2006 - Issue 3
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Original Articles

Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study

M. Vračko European Chemical Bureau, Institute for Health and Consumer Protection, European Commission Joint Research Centre, 21020 Ispra, Italy; Kemijski inštitut/National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, SloveniaCorrespondence[email protected]
,
V. Bandelj Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, B. go Grotta Gigante-Briščiki 42/C, Sgonico-Zgonik (TS), Italy
,
P. Barbieri Department of Chemical Sciences, University of Trieste, Via L. Giorgieri 1, I-34127 Trieste, Italy
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E. Benfenati Istituto di Ricerche Farmacologiche Mario Negri, Via Eritrea 62, 20157 Milano, Italy
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Q. Chaudhry Central Science Laboratory, Sand Hutton, York YO41 1LZ, UK
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M. Cronin School of Pharmacy and Chemistry, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK
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J. Devillers CTIS, 3 Chemin de la Gravière, 69140 Rillieux La Pape, France
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A. Gallegos European Chemical Bureau, Institute for Health and Consumer Protection, European Commission Joint Research Centre, 21020 Ispra, Italy
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G. Gini Department of Electronic and Informatics, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy
,
P. Gramatica Department of Structural and Functional Biology, University of Insubria, Via J.H. Dunant 3, I-21100 Varese, Italy
,
C. Helma In silico toxicology, Talstrasse 20, D-79102 Freiburg, Germany
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P. Mazzatorta Department of BioAnalytical Science, Nestlè Research Center, Vers-Chez-les-Blanc 44, 1000 Lausanne 26, Switzerland
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D. Neagu Department of Computing, School of Informatics, University of Bradford, BD7 1DP, UK
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T. Netzeva European Chemical Bureau, Institute for Health and Consumer Protection, European Commission Joint Research Centre, 21020 Ispra, Italy
,
M. Pavan European Chemical Bureau, Institute for Health and Consumer Protection, European Commission Joint Research Centre, 21020 Ispra, Italy
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G. Patlewicz European Chemical Bureau, Institute for Health and Consumer Protection, European Commission Joint Research Centre, 21020 Ispra, Italy
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M. Randić Kemijski inštitut/National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
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I. Tsakovska European Chemical Bureau, Institute for Health and Consumer Protection, European Commission Joint Research Centre, 21020 Ispra, Italy
&
A. Worth European Chemical Bureau, Institute for Health and Consumer Protection, European Commission Joint Research Centre, 21020 Ispra, Italy
 show all
Pages 265-284 | Received 19 Jan 2006, Accepted 25 Apr 2006, Published online: 01 Feb 2007

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P.V. Pogodin, A.A. Lagunin, D.A. Filimonov, M.C. Nicklaus & V.V. Poroikov. (2019) Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing. SAR and QSAR in Environmental Research 30:10, pages 759-773.
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M. Vračko & V. Drgan. (2017) Grouping of CoMPARA data with respect to compounds from the carcinogenic potency database. SAR and QSAR in Environmental Research 28:10, pages 801-813.
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V. Drgan, Š. Župerl, M. Vračko, F. Como & M. Novič. (2016) Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm. SAR and QSAR in Environmental Research 27:7, pages 501-519.
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J. Devillers & E. Mombelli. (2010) Evaluation of the OECD QSAR Application Toolbox and Toxtree for estimating the mutagenicity of chemicals. Part 2. α-β unsaturated aliphatic aldehydes. SAR and QSAR in Environmental Research 21:7-8, pages 771-783.
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J. Devillers & E. Mombelli. (2010) Evaluation of the OECD QSAR Application Toolbox and Toxtree for estimating the mutagenicity of chemicals. Part 1. Aromatic amines. SAR and QSAR in Environmental Research 21:7-8, pages 753-769.
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M. Bolčič–Tavčar & M. Vračko. (2009) Assessing the reproductive toxicity of some (con)azole compounds using a structure–activity relationship approach. SAR and QSAR in Environmental Research 20:7-8, pages 711-725.
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X. Chen, Y.Z. Liang, D.L. Yuan & Q.S. Xu. (2009) A modified uncorrelated linear discriminant analysis model coupled with recursive feature elimination for the prediction of bioactivity. SAR and QSAR in Environmental Research 20:1-2, pages 1-26.
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E. Benfenati. (2007) The specificity of the QSAR models for regulatory purposes: the example of the DEMETRA project† . SAR and QSAR in Environmental Research 18:3-4, pages 209-220.
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A. P. Worth, A. Bassan, J. De Bruijn, A. Gallegos Saliner, T. Netzeva, M. Pavan, G. Patlewicz, I. Tsakovska & S. Eisenreich. (2007) The role of the European Chemicals Bureau in promoting the regulatory use of (Q)SAR methods† . SAR and QSAR in Environmental Research 18:1-2, pages 111-125.
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Donald J. AbrahamAlexander Tropsha. 2003. Burger's Medicinal Chemistry and Drug Discovery. Burger's Medicinal Chemistry and Drug Discovery 1 30 .
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Marjan Vračko & Jure Zupan. (2015) A non-standard view on artificial neural networks. Chemometrics and Intelligent Laboratory Systems 149, pages 140-152.
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Alexander V. LyubimovRodolpho C. Braga, Vinicius M. Alves, Flavia C. Silva & Carolina H. Andrade. 2011. Encyclopedia of Drug Metabolism and Interactions. Encyclopedia of Drug Metabolism and Interactions 1 28 .
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Ovanes MekenyanM. T. D. Cronin. 2010. In Silico Toxicology. In Silico Toxicology 275 300 .
Donald J. AbrahamAlexander Tropsha. 2003. Burger's Medicinal Chemistry and Drug Discovery. Burger's Medicinal Chemistry and Drug Discovery 505 534 .
Alexander Tropsha. (2010) Best Practices for QSAR Model Development, Validation, and Exploitation. Molecular Informatics 29:6-7, pages 476-488.
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Marjana Novič & Marjan Vračko. (2010) QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity. Molecules 15:3, pages 1987-1999.
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Igor Kuzmanovski, Marjana Novič & Mira Trpkovska. (2009) Automatic adjustment of the relative importance of different input variables for optimization of counter-propagation artificial neural networks. Analytica Chimica Acta 642:1-2, pages 142-147.
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Charles Pittinger & Asish Mohapatra. 2009. Information Resources in Toxicology. Information Resources in Toxicology 631 638 .
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Ramon Carbó-Dorca & Ana Gallegos. 2009. Encyclopedia of Complexity and Systems Science. Encyclopedia of Complexity and Systems Science 7422 7480 .
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Alexander Tropsha. 2008. Chemoinformatics Approaches to Virtual Screening. Chemoinformatics Approaches to Virtual Screening 295 325 .
Liying Zhang, Hao Zhu, Tudor I. Oprea, Alexander Golbraikh & Alexander Tropsha. (2008) QSAR Modeling of the Blood–Brain Barrier Permeability for Diverse Organic Compounds. Pharmaceutical Research 25:8, pages 1902-1914.
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N. Fedorova, Yu. Zupan, M. Novic, M. Vracko, M. Tushar & T. Dyankova. (2008) Neural network models for predicting the properties of chemical compounds. Fibre Chemistry 40:3, pages 281-286.
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James Devillers. 2009. Artificial Neural Networks. Artificial Neural Networks 59 77 .
Grace Patlewicz, Aynur O. Aptula, David W. Roberts & Eugenio Uriarte. (2008) A Minireview of Available Skin Sensitization (Q)SARs/Expert Systems. QSAR & Combinatorial Science 27:1, pages 60-76.
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Sisir Nandi, Marjan Vracko & Manish C. Bagchi. (2007) Anticancer Activity of Selected Phenolic Compounds: QSAR Studies Using Ridge Regression and Neural Networks. Chemical Biology & Drug Design 70:5, pages 424-436.
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Uko Maran, Sulev Sild, Paolo Mazzatorta, Mos Casalegno, Emilio Benfenati & Mathilde Romberg. 2007. Distributed, High-Performance and Grid Computing in Computational Biology. Distributed, High-Performance and Grid Computing in Computational Biology 60 74 .

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