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admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties

Journal of chemical information and modeling, 2012-11, Vol.52 (11), p.3099-3105

2012

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China: Forward to the Green Pesticides via a Basic Research Program

Journal of agricultural and food chemistry, 2010-03, Vol.58 (5), p.2613-2623

2010

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Classification of Cytochrome P450 Inhibitors and Noninhibitors Using Combined Classifiers

Journal of chemical information and modeling, 2011-05, Vol.51 (5), p.996-1011

2011

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In silico prediction of chemical toxicity on avian species using chemical category approaches

Chemosphere (Oxford), 2015-03, Vol.122, p.280-287

2015

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Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods

Journal of cheminformatics, 2023-03, Vol.15 (1), p.35-35, Article 35

2023

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In silico estimation of chemical aquatic toxicity on crustaceans using chemical category methods

Environmental science--processes & impacts, 2018-01, Vol.20 (9), p.1234-1243

2018

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In silico prediction of UGT-mediated metabolism in drug-like molecules via graph neural network

Journal of cheminformatics, 2022-07, Vol.14 (1), p.46-46, Article 46

2022

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cis-Configuration: A New Tactic/Rationale for Neonicotinoid Molecular Design

Journal of agricultural and food chemistry, 2011-04, Vol.59 (7), p.2943-2949

2011

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Green Pesticide R&D in China

Journal of agricultural and food chemistry, 2023-04, Vol.71 (14), p.5417-5418

2023

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In silico prediction of hERG potassium channel blockage by chemical category approaches

Toxicology research (Cambridge), 2016-01, Vol.5 (2), p.570-582

2016

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IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method

Journal of chemical information and modeling, 2022-06, Vol.62 (11), p.2788-2799

2022

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Computational Prediction of Site of Metabolism for UGT-Catalyzed Reactions

Journal of chemical information and modeling, 2019-03, Vol.59 (3), p.1085-1095

2019

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In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method

Molecular informatics, 2016-04, Vol.35 (3-4), p.136-144

2016

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Multiclassification Prediction of Enzymatic Reactions for Oxidoreductases and Hydrolases Using Reaction Fingerprints and Machine Learning Methods

Journal of chemical information and modeling, 2018-06, Vol.58 (6), p.1169-1181

2018

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In silico Prediction of Chemical Ames Mutagenicity

Journal of chemical information and modeling, 2012-11, Vol.52 (11), p.2840-2847

2012

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Correction to “admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties”

Journal of chemical information and modeling, 2019-11, Vol.59 (11), p.4959-4959

2019

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In Silico Assessment of Chemical Biodegradability

Journal of chemical information and modeling, 2012-03, Vol.52 (3), p.655-669

2012

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In silico prediction of chemical aquatic toxicity for marine crustaceans via machine learning

Toxicology research (Cambridge), 2019-05, Vol.8 (3), p.341-352

2019

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In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods

Chemosphere (Oxford), 2011-03, Vol.82 (11), p.1636-1643

2011

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Prediction of human genes and diseases targeted by xenobiotics using predictive toxicogenomic-derived models (PTDMs)

Molecular bioSystems, 2013-01, Vol.9 (6), p.1316-1325

2013

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Insights into Molecular Basis of Cytochrome P450 Inhibitory Promiscuity of Compounds

Journal of chemical information and modeling, 2011-10, Vol.51 (10), p.2482-2495

2011

Volltextzugriff (PDF)

In silico estimation of chemical aquatic toxicity on crustaceans using chemical category methodsElectronic supplementary information (ESI) available. See DOI: 10.1039/c8em00220g

2018-09

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Rapid determination of melamine in soil and strawberry by liquid chromatography–tandem mass spectrometry

Food control, 2011-10, Vol.22 (10), p.1629-1633

2011

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In silico prediction of chemical aquatic toxicity with chemical category approaches and substructural alerts

Toxicology research (Cambridge), 2015-01, Vol.4 (2), p.452-463

2015

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prediction of chemical aquatic toxicity for marine crustaceans machine learning

Toxicology research (Cambridge), 2019-05, Vol.8 (3), p.341-352

2019

Volltextzugriff (PDF)

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