Using fragment chemistry data mining and probabilistic neural networks in screening chemicals for acute toxicity to the fathead minnow

SAR and QSAR in Environmental Research
S P NiculescuM Lewis

Abstract

The paper is illustrating how the general data mining methodology may be adapted to provide solutions to the problem of high throughput virtual screening of organic chemicals for possible acute toxicity to the fathead minnow fish. The present approach involves mining fragment information from chemical structures and is using probabilistic neural networks to model the relationship between structure and toxicity. Probabilistic neural networks implement a special class of multivariate non-linear Bayesian statistical models. The mathematical principles supporting their use for value prediction purposes are clarified and their peculiarities discussed. As part of the research phase of the data mining process, a dataset consisting of 800 structures and associated fathead minnow (Pimephales promelas) 96-h LC50 acute toxicity endpoint information is used for both the purpose of identifying an advantageous combination of fragment descriptors and for training the neural networks. As a result, two powerful models are generated. Model 1 implements the basic PNN with Gaussian kernel (statistical corrections included) while Model 2 implements the PNN with Gaussian kernel and separated variables. External validation is performed using a separa...Continue Reading

References

Aug 19, 2000·Archives of Environmental Contamination and Toxicology·S P NiculescuT W Schultz
Jul 1, 1996·Neural Networks : the Official Journal of the International Neural Network Society·Shuenn Shyang Wang, Wen Gou Lin

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Citations

Mar 3, 2007·Nature Reviews. Drug Discovery·William LogingBryn Williams-Jones
Dec 9, 2008·SAR and QSAR in Environmental Research·S P NiculescuJ Tigner
Nov 8, 2005·SAR and QSAR in Environmental Research·J Devillers
Feb 26, 2016·SAR and QSAR in Environmental Research·X WuJ Hu
Mar 18, 2015·SAR and QSAR in Environmental Research·M CassottiV Consonni
Oct 15, 2008·SAR and QSAR in Environmental Research·A Maunz, C Helma
Feb 16, 2021·Regulatory Toxicology and Pharmacology : RTP·Enrico Mombelli, Pascal Pandard

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