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Quantitative structure–activity relationship
Results: 399

#	Item
311	AGENDA for Jan 29-Feb 1, 2013 FIFRA SAP Meeting Add to Reading List Source URL: www.epa.gov Language: English - Date: 2013-01-25 14:06:27 Assay Biochemistry Titration United States Environmental Protection Agency Endocrine disruptor Pesticide Quantitative structure–activity relationship Chemistry Science Laboratory techniques
312	Binning as a Screening Process for the Universe to the PCCL - Report for the NDWAC CCL Work Group Plenary Meeting September 17-18, 2003 Add to Reading List Source URL: www.epa.gov Language: English - Date: 2009-07-30 15:20:05 Computational chemistry Medicinal chemistry Pharmacology Quantitative structure–activity relationship Solubility Science Binning Chemistry Solutions Cheminformatics
313	SAR and QSAR in Environmental Research, Vol. 16, No. 4, August 2005, 339–347 An in silico ensemble method for lead discovery: decision forest H. HONG†, W. TONG‡, Q. XIE†, H. FANG† and R. PERKINS† †Divisio Add to Reading List Source URL: www.fda.gov Language: English* Drug discovery Cheminformatics Machine learning Medicinal chemistry Quantitative structure–activity relationship Decision tree learning In silico Chemical library Virtual screening Pharmaceutical sciences Science Pharmacology
314	US EPA: OSWER: Risk Assessment Guidance for Superfund, January[removed]Appendix C Add to Reading List Source URL: www.epa.gov Language: English - Date: 2012-12-18 12:29:54 Science Risk Pharmacokinetics Pharmacy Physiologically based pharmacokinetic modelling Toxicokinetics Risk assessment Quantitative structure–activity relationship Scientific Time Sharing Corporation Pharmaceutical sciences Toxicology Pharmacology
315	J. Chem. Inf. Comput. Sci. 1998, 38, [removed]Evaluation of Quantitative Structure-Activity Relationship Methods for Large-Scale Prediction of Chemicals Binding to the Estrogen Receptor† Add to Reading List Source URL: www.fda.gov Language: English Pharmaceutical sciences Medicinal chemistry Computational chemistry Pharmacology Drug discovery Quantitative structure–activity relationship Molecular descriptor Drug design Structure–activity relationship Chemistry Science Cheminformatics
316	Assessment of Prediction Confidence and Domain Extraolation of Two Structure-Active Relationship Models for Predicting Estrogen Receptor Binding Activity Add to Reading List Source URL: www.fda.gov Language: English Medicinal chemistry Chemistry Cheminformatics Computational chemistry Clinical research Quantitative structure–activity relationship Applicability Domain Drug discovery Cross-validation Pharmaceutical sciences Pharmacology Science
317	Mutagenesis vol. 19 no. 5 pp[removed], 2004 doi:[removed]mutage/geh043 Three new consensus QSAR models for the prediction of Ames genotoxicity Add to Reading List Source URL: www.fda.gov Language: English Medicinal chemistry Pharmacology Mathematical chemistry Computational chemistry Quantitative structure–activity relationship Molecular descriptor Topological index Cross-validation Applicability Domain Chemistry Cheminformatics Science
318	Pure Appl. Chem., Vol. 75, Nos. 11–12, pp. 2375–2388, 2003. © 2003 IUPAC Workshop 1.2 Regulatory application of SAR/QSAR for priority setting of endocrine disruptors: A perspective* Add to Reading List Source URL: www.fda.gov Language: English Science Cheminformatics Pharmacology Computational chemistry Quantitative structure–activity relationship Pharmacophore Endocrine disruptor Biological activity Structure–activity relationship Pharmaceutical sciences Medicinal chemistry Chemistry
319	Environmental Toxicology and Chemistry, Vol. 22, No. 8, pp. 000–000, 2003 q 2003 SETAC Printed in the USA[removed] $[removed]Annual Review Add to Reading List Source URL: www.fda.gov Language: English Cheminformatics Medicinal chemistry Computational chemistry Pharmacology Drug discovery Quantitative structure–activity relationship Chemometrics Chemical database Structure–activity relationship Chemistry Science Pharmaceutical sciences
320	J. Chem. Inf. Comput. Sci. 2003, 43, [removed]Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models Add to Reading List Source URL: www.fda.gov Language: English Computational statistics Quantitative structure–activity relationship Decision tree learning Bootstrap aggregating CHAID Artificial neural network ADAPA Pruning Decision tree model Machine learning Decision trees Statistics

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