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Original Articles

A General QSAR Model for Predicting the Acute Toxicity of Pesticides to Oncorhynchus mykiss

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Pages 25-43 | Received 28 May 1999, Accepted 05 Aug 1999, Published online: 24 Sep 2006

References

  • Hansch , C. , Maloney , P. P. , Fujita , T. and Muir , R. M. 1962 . Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. . Nature , 194 : 178 – 180 .
  • Hansch , C. and Fujita , T. 1964 . p-σ-τ Analysis. A method for the correlation of biological activity and chemical structure. . J. Am. Chem. Soc. , 86 : 1616 – 1626 .
  • Free , S. M. and Wilson , J. W. 1964 . A mathematical contribution to structure-activity studies. . J. Med. Chem. , 1 : 395 – 399 .
  • Devillers , J. and Lipnick , R. L. 1990 . “ Practical applications of regression analysis in environmental QSAR studies. In, Practical Applications of Quantitative Structure-Activity Relationships (QSAR) in Environmental Chemistry and Toxicology ” . Edited by: Karcher , W. and Devillers , J. 129 – 143 . Dordrecht : Kluwer Academic Publishers .
  • Schultz , T. W. , Sinks , G. D. and Bearden , A. P. 1998 . “ QSAR in aquatic toxicology: A mechanism of action approach comparing toxic potency to Pimephales promelas, Tetrahymena pyriformis, and Vibrio fischeri. ” . In Comparative QSAR , Edited by: Devillers , J. 51 – 109 . Philadelphia : Taylor and Francis .
  • Hansch , C. , Gao , H. and Hoekman , D. 1998 . “ A generalized approach to comparative QSAR ” . In Comparative QSAR , Edited by: Devillers , J. 285 – 368 . Philadelphia : Taylor and Francis .
  • Eberhart , R. C. and Dobbins , R. W. 1990 . Neural Network PC Tools: A Practical Guide , 414 San Diego : Academic Press .
  • Wasserman , P. D. 1993 . Advanced Methods in Neural Computing , 255 New York : Van Nostrand Reinhold .
  • Jodouin , J. F. 1994 . Les Réseaux de Neurones. Principes et Définitions , 124 Paris : Hermès .
  • de Saint Laumer , J. Y. , Chastrette , M. and Devillers , J. 1991 . “ Multilayer neural networks applied to structure-activity relationships. ” . In Applied Multivariate Analysis in SAR and Environmental Studies , Edited by: Devillers , J. and Karcher , W. 479 – 521 . Dordrecht : Kluwer Academic Publishers .
  • Chastrette , M. , de Saint Laumer , J. Y. and Peyraud , J. F. 1993 . Adapting the structure of a neural network to extract chemical information. Application to structure-odour relationships. . SAR QSAR Environ. Res. , 1 : 221 – 231 .
  • Devillers , J. , Bintein , S. , Domine , D. and Karcher , W. 1995 . A general QSAR model for predicting the toxicity of organic chemicals to luminescent bacteria (Microtox® test). . SAR QSAR Environ. Res. , 4 : 29 – 38 .
  • Devillers , J. 1996 . Neural Networks in QSAR and Drug Design , 284 London : Academic Press .
  • Kaiser , K. L. E. , Niculescu , S. P. and Schüürmann , G. 1997 . Feed forward backpropagation neural networks and their use in predicting the acute toxicity of chemicals to the fathead minnow. . Water Qual. Res. J. Canada , 32 : 637 – 657 .
  • Zakarya , D. , Boulaamail , A. , Larfaoui , E. M. and Lakhlifi , T. 1997 . QSARs for toxicity of DDT-type analogs using neural network. . SAR QSAR Environ. Res. , 6 : 183 – 203 .
  • Eldred , D. V. and Jurs , P. C. 1999 . Prediction of acute mammalian toxicity of organophosphorus pesticide compounds from molecular structure. . SAR QSAR Environ. Res. , 10 : 75 – 99 .
  • Devillers , J. and Domine , D. 1999 . A noncongeneric model for predicting toxicity of organic molecules to . Vibrio fischeri. SAR QSAR Environ. Res. , 10 : 61 – 70 .
  • Devillers , J. 2000 . Prediction of toxicity of organophosphorus insecticides against the midge . Chironomus riparius , via a QSAR neural network model integrating environmental variables. (Submitted).
  • Mayer , F. L. and Ellersieck , M. R. 1986 . “ Manual of Acute Toxicity: Interpretation and Data Base for 410 Chemicals and 66 Species of Freshwater Animals. ” . 160 506 U.S. Fish Wildl. Serv., Resour. Publ. .
  • Shiu , W. Y. , Ma , K. C. , Mackay , D. , Seiber , J. N. and Wauchope , R. D. 1990 . Solubilities of pesticide chemicals in water. Part I: Environmental physical chemistry. . Rev. Environ. Contam. Toxicol , 116 : 35 – 221 .
  • Montgomery , J. H. 1993 . Agrochemicals Desk Reference. Environmental Data , 625 Boca Raton : Lewis Publishers .
  • Tomlin , C. 1994 . The Pesticide Manual. Incorporating the Agrochemicals Handbook , Tenth Edition 1341 UK : The British Crop Protection Council and The Royal Society of Chemistry .
  • Moreau , G. and Broto , P. 1980 . The autocorrelation of a topological structure: A new molecular descriptor. . Nouv. J. Chim. , 4 : 359 – 360 .
  • Moreau , G. and Broto , P. 1980 . Autocorrelation of molecular structures, application to SAR studies. . Nouv. J. Chim. , 4 : 757 – 764 .
  • Broto , P. and Devillers , J. 1990 . “ Autocorrelation of properties distributed on molecular graphs. In, Practical Applications of Quantitative Structure-Activity Relationships (QSAR) in Environmental Chemistry and Toxicology ” . Edited by: Karcher , W. and Devillers , J. 105 – 127 . Dordrecht : Kluwer Academic Publishers .
  • Devillers , J. 1999 . “ Autocorrelation descriptors for modeling (eco)toxicological endpoints. ” . In Topological Indices and Related Descriptors in QSAR and QSPR , Edited by: Devillers , J. and Balaban , A. T. 595 – 612 . The Netherlands : Gordon and Breach .
  • Rekker , R. F. and Mannhold , R. 1992 . “ Calculation of Drug Lipophilicity. The Hydrophobic Fragmental Constant Approach. ” . 112 Weinheim : VCH .
  • Hansch , C. and Leo , A. 1979 . “ Substituent Constants for Correlation Analysis in Chemistry and Biology ” . 339 New York : J. Wiley & Sons .
  • “ AUTOCOR ” . In CTIS, 3 Chemin de la Gravière , France : 69140 Rillieux La Pape . (Version 2.40).
  • Rumelhart , D. E. , Hinton , G. E. and Williams , R. J. 1986 . Learning representations by back-propagating errors. . Nature , 323 : 533 – 536 .
  • Devillers , J. 1996 . “ Strengths and weaknesses of the backpropagation neural network in QSAR and QSPR studies. ” . In Neural Networks in QSAR and Drug Design , Edited by: Devillers , J. 1 – 46 . London : Academic Press .
  • “ STATQSAR ” . In Package. CTIS, 3 Chemin de la Gravière , France : 69140 Rillieux La Pape .
  • Hair , J. F. , Anderson , R. E. , Tatham , R. L. and Black , W. C. 1992 . Multivariate Data Analysis with Readings. , Third Edition 544 New York : Macmillan Publishing Company .
  • Lek , S. , Delacoste , M. , Baran , P. , Dimopoulos , I. , Lauga , J. and Aulagnier , S. 1996 . Application of neural networks to modelling nonlinear relationships in ecology. . Ecol. Model. , 90 : 39 – 52 .
  • Vila , J. P. , Wagner , V. , Neveu , P. , Voltz , M. and Lagacherie , P. 1999 . Neural network architecture selection: New Bayesian perspectives in predictive modelling. Application to a soil hydrology problem. . Ecol. Model. , 120 : 119 – 130 .
  • Moatar , F. , Fessant , F. and Poirel , A. 1999 . pH modelling by neural networks. Application of control and validation data series in the Middle Loire river. . Ecol. Model , 120 : 141 – 156 .
  • Dimopoulos , I. , Chronopoulos , J. , Chronopoulos-Sereli , A. and Lek , S. 1999 . Neural network models to study relationships between lead concentration in grasses and permanent urban descriptors in Athens city (Greece). . Ecol. Model , 120 : 157 – 165 .
  • Barciela , R. M. , Garcia , E. and Fernandez , E. 1999 . Modelling primary production in a coastal embayment affected by upwelling using dynamic ecosystem models and artificial neural networks. . Ecol Model. , 120 : 199 – 211 .
  • Scardi , M. and Harding , L. W. 1999 . Developing an empirical model of phytoplankton primary production: A neural network case study. . Ecol. Model. , 120 : 213 – 223 .
  • Gross , L. , Thiria , S. and Frouin , R. 1999 . Applying artificial neural network methodology to ocean color remote sensing. . Ecol Model. , 120 : 237 – 246 .
  • Lek-Ang , S. , Deharveng , L. and Lek , S. 1999 . Predictive models of collembolan diversity and abundance in a riparian habitat. . Ecol. Model. , 120 : 247 – 260 .
  • Aoki , I. , Komatsu , T. and Hwang , K. 1999 . Prediction of response of zooplankton biomass to climatic and oceanic changes. . Ecol. Model. , 120 : 261 – 270 .
  • Schleiter , I. M. , Borchardt , D. , Wagner , R. , Dapper , T. , Schmidt , K. D. , Schmidt , H. H. and Werner , H. 1999 . Modelling water quality, bioindication and population dynamics in lotic ecosystems using neural networks. . Ecol. Model. , 120 : 271 – 286 .
  • Brosse , S. , Guegan , J. F. , Tourenq , J. N. and Lek , S. 1999 . The use of artificial neural networks to assess fish abundance and spacial occupancy in the littoral zone of a mesotrophic lake. . Ecol Model , 120 : 299 – 311 .
  • Laë , R. , Lek , S. and Moreau , J. 1999 . Predicting fish yield of African lakes using neural networks. . Ecol Model. , 120 : 325 – 335 .
  • Manel , S. , Dias , J. M. and Ormerod , S. J. 1999 . Comparing discriminant analysis, neural networks and logistic regression for predicting species distribution: A case study with a Himalayan river bird. . Ecol Model. , 120 : 337 – 347 .
  • Tourenq , C. , Aulagnier , S. , Mesléard , F. , Durieux , L. , Johnson , A. , Gonzalez , G. and Lek , S. 1999 . Use of artificial neural networks for predicting rice crop damage by greater flamingos in the Camargue, France. . Ecol. Model. , 120 : 349 – 358 .

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