| Prediction of n-octanol/water partition coefficients for polychlorinated dibenzo-p-dioxins using a general regression neural network. | |
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MedLine Citation:
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PMID: 12761606 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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A general regression neural network was used for the first time to study quantitative structure and property relationships of organic pollutants to correlate and predict n-octanol/water partition coefficients of polychlorinated dibenzo- p -dioxins from their topological molecular descriptors. In total, 42 polychlorinated dibenzo- p -dioxins and dibenzo- p -dioxins were available for this study-42 polychlorinated dibenzo- p -dioxins and dibenzo- p -dioxins in the training data set and 41 polychlorinated dibenzo- p -dioxins in the test data set. Partial least squares regression, back propagation network and general regression neural network models were trained using the training data set, and the accuracy of the models obtained were examined by the use of leave-one-out cross-validation. For prediction of the n-octanol/water partition coefficient, the best method is the general regression neural network. With the test data set, the correlation coefficient, root mean square error and mean absolute relative error for the general regression neural network model are 0.9276, 0.22 and 2.79%, respectively. For describing the structure of polychlorinated dibenzo- p -dioxins, the topological molecular descriptors outperform the mobile order and disorder thermodynamic method. |
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Authors:
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G Zheng; W H Huang; X H Lu |
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Publication Detail:
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Type: Comparative Study; Evaluation Studies; Journal Article; Validation Studies Date: 2003-05-22 |
Journal Detail:
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Title: Analytical and bioanalytical chemistry Volume: 376 ISSN: 1618-2642 ISO Abbreviation: Anal Bioanal Chem Publication Date: 2003 Jul |
Date Detail:
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Created Date: 2003-07-07 Completed Date: 2003-10-30 Revised Date: 2006-11-15 |
Medline Journal Info:
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Nlm Unique ID: 101134327 Medline TA: Anal Bioanal Chem Country: Germany |
Other Details:
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Languages: eng Pagination: 680-5 Citation Subset: IM |
Affiliation:
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School of Environmental Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, P.R. China. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Binding Sites Computer Simulation Models, Molecular* Molecular Conformation Neural Networks (Computer)* Octanols / chemistry* Reproducibility of Results Sensitivity and Specificity Soil Pollutants Solubility Solutions / chemistry Tetrachlorodibenzodioxin / analogs & derivatives*, chemistry* Water / chemistry* |
| Chemical | |
Reg. No./Substance:
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0/Octanols; 0/Soil Pollutants; 0/Solutions; 0/polychlorodibenzo-4-dioxin; 1746-01-6/Tetrachlorodibenzodioxin; 7732-18-5/Water |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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