ToxCast EPA in Vitro to in Vivo Challenge: Insight into the Rank-I Model
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Igor V. Tetko | Sergii Novotarskyi | Robert Körner | I. Tetko | S. Novotarskyi | R. Körner | A. Abdelaziz | Ahmed Abdelaziz | Yurii Sushko | Joachim Vogt | Yurii Sushko | Joachim Vogt
[1] I. Tetko,et al. Spatiotemporal activity patterns of rat cortical neurons predict responses in a conditioned task. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[2] Igor V Tetko,et al. Prediction of logP for Pt(II) and Pt(IV) complexes: Comparison of statistical and quantum-chemistry based approaches. , 2016, Journal of inorganic biochemistry.
[3] Igor V. Tetko,et al. Efficient Partition of Learning Data Sets for Neural Network Training , 1997, Neural Networks.
[4] Dragos Horvath,et al. Design of a General‐Purpose European Compound Screening Library for EU‐OPENSCREEN , 2014, ChemMedChem.
[5] I. Tetko,et al. ISIDA - Platform for Virtual Screening Based on Fragment and Pharmacophoric Descriptors , 2008 .
[6] Igor V Tetko,et al. Identifying potential endocrine disruptors among industrial chemicals and their metabolites--development and evaluation of in silico tools. , 2015, Chemosphere.
[7] Igor V Tetko,et al. A comparison of different QSAR approaches to modeling CYP450 1A2 inhibition , 2011, J. Chem. Inf. Model..
[8] Igor V Tetko,et al. Calculation of lipophilicity for Pt(II) complexes: experimental comparison of several methods , 2008, Chemistry Central Journal.
[9] Roberto Todeschini,et al. Handbook of Molecular Descriptors , 2002 .
[10] Vladimir Potemkin,et al. A new paradigm for pattern recognition of drugs , 2008, J. Comput. Aided Mol. Des..
[11] I. Tetko,et al. Extended Functional Groups (EFG): An Efficient Set for Chemical Characterization and Structure-Activity Relationship Studies of Chemical Compounds , 2015, Molecules.
[12] L. Hall,et al. Molecular Structure Description: The Electrotopological State , 1999 .
[13] Igor V. Tetko,et al. Benchmarking of Linear and Nonlinear Approaches for Quantitative Structure-Property Relationship Studies of Metal Complexation with Ionophores , 2006, J. Chem. Inf. Model..
[14] Igor V Tetko,et al. Using Online Tool (iPrior) for Modeling ToxCast™ Assays Towards Prioritization of Animal Toxicity Testing. , 2015, Combinatorial chemistry & high throughput screening.
[15] S. V. Antonenko,et al. HIV-1 reverse transcriptase inhibitor design using artificial neural networks. , 1994, Journal of medicinal chemistry.
[16] Igor V. Tetko,et al. Neural Network Studies, 2. Variable Selection , 1996, J. Chem. Inf. Comput. Sci..
[17] David Dix,et al. Computational Toxicology as Implemented by the U.S. EPA: Providing High Throughput Decision Support Tools for Screening and Assessing Chemical Exposure, Hazard and Risk , 2010, Journal of toxicology and environmental health. Part B, Critical reviews.
[18] Igor V. Tetko,et al. Neural Network Studies, 4. Introduction to Associative Neural Networks , 2002, J. Chem. Inf. Comput. Sci..
[19] Russell Reed,et al. Pruning algorithms-a survey , 1993, IEEE Trans. Neural Networks.
[20] Igor V. Tetko,et al. Development of Dimethyl Sulfoxide Solubility Models Using 163 000 Molecules: Using a Domain Applicability Metric to Select More Reliable Predictions , 2013, J. Chem. Inf. Model..
[21] Igor V. Tetko,et al. Neural Network Studies. 3. Variable Selection in the Cascade-Correlation Learning Architecture , 1998, J. Chem. Inf. Comput. Sci..
[22] Igor V. Tetko,et al. How Accurately Can We Predict the Melting Points of Drug-like Compounds? , 2014, J. Chem. Inf. Model..
[23] Lemont B. Kier,et al. Electrotopological State Indices for Atom Types: A Novel Combination of Electronic, Topological, and Valence State Information , 1995, J. Chem. Inf. Comput. Sci..
[24] Igor V. Tetko,et al. Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis , 2008, J. Chem. Inf. Model..
[25] Igor V. Tetko,et al. The perspectives of computational chemistry modeling , 2011, Journal of Computer-Aided Molecular Design.
[26] Igor V. Tetko,et al. Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information , 2011, J. Comput. Aided Mol. Des..
[27] Gregg D. Wilensky,et al. Neural Network Studies , 1993 .
[28] Raimund Mannhold,et al. Large‐Scale Evaluation of log P Predictors: Local Corrections May Compensate Insufficient Accuracy and Need of Experimentally Testing Every Other Compound , 2009, Chemistry & biodiversity.
[29] Igor V. Tetko,et al. Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection , 2008, J. Chem. Inf. Model..
[30] I. Tetko,et al. QSAR models and scaffold-based analysis of non-nucleoside HIV RT inhibitors , 2015 .
[31] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[32] David M. Reif,et al. In Vitro Screening of Environmental Chemicals for Targeted Testing Prioritization: The ToxCast Project , 2009, Environmental health perspectives.
[33] Igor V. Tetko,et al. A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 2. Application to simultaneous single unit recordings , 2001, Journal of Neuroscience Methods.
[34] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[35] Johann Gasteiger,et al. Of molecules and humans. , 2006, Journal of medicinal chemistry.
[36] Igor V. Tetko,et al. Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set , 2010, J. Chem. Inf. Model..
[37] A. Cherkasov. Inductive Descriptors: 10 Successful Years in QSAR , 2005 .
[38] Gerhard Klebe,et al. Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures , 1994, J. Chem. Inf. Comput. Sci..
[39] Tom Tollenaere,et al. SuperSAB: Fast adaptive back propagation with good scaling properties , 1990, Neural Networks.
[40] Elie Bienenstock,et al. Neural Networks and the Bias/Variance Dilemma , 1992, Neural Computation.
[41] Igor V. Tetko,et al. Application of a Pruning Algorithm To Optimize Artificial Neural Networks for Pharmaceutical Fingerprinting , 1998, J. Chem. Inf. Comput. Sci..
[42] Igor V. Tetko,et al. Neural network studies, 1. Comparison of overfitting and overtraining , 1995, J. Chem. Inf. Comput. Sci..
[43] Igor V. Tetko,et al. Modeling the Biodegradability of Chemical Compounds Using the Online CHEmical Modeling Environment (OCHEM) , 2013, Molecular informatics.
[44] Egon L. Willighagen,et al. The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics , 2003, J. Chem. Inf. Comput. Sci..
[45] I. Tetko,et al. Applicability domain for in silico models to achieve accuracy of experimental measurements , 2010 .
[46] Igor I. Baskin,et al. Chemical graphs and their basis invariants , 1999 .
[47] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[48] David Vidal,et al. LINGO, an Efficient Holographic Text Based Method To Calculate Biophysical Properties and Intermolecular Similarities , 2005, J. Chem. Inf. Model..