Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties

10.2174/138955707782331696

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Main Authors:	Yap, C.W., Li, H., Ji, Z.L., Chen, Y.Z.
Other Authors:	PHARMACY
Format:	Article
Published:	2014
Subjects:	ADME ADMET Compound Drug Pharmacodynamics Pharmacokinetics QSAR QSPR Statistical learning methods Structure-activity relationship Toxicity
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/106296
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-106296
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spelling	sg-nus-scholar.10635-1062962023-10-31T07:17:47Z Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties Yap, C.W. Li, H. Ji, Z.L. Chen, Y.Z. PHARMACY ADME ADMET Compound Drug Pharmacodynamics Pharmacokinetics QSAR QSPR Statistical learning methods Structure-activity relationship Toxicity 10.2174/138955707782331696 Mini-Reviews in Medicinal Chemistry 7 11 1097-1107 MMCIA 2014-10-29T01:58:01Z 2014-10-29T01:58:01Z 2007-11 Article Yap, C.W., Li, H., Ji, Z.L., Chen, Y.Z. (2007-11). Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties. Mini-Reviews in Medicinal Chemistry 7 (11) : 1097-1107. ScholarBank@NUS Repository. https://doi.org/10.2174/138955707782331696 13895575 http://scholarbank.nus.edu.sg/handle/10635/106296 000250698700002 Scopus
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	ADME ADMET Compound Drug Pharmacodynamics Pharmacokinetics QSAR QSPR Statistical learning methods Structure-activity relationship Toxicity
spellingShingle	ADME ADMET Compound Drug Pharmacodynamics Pharmacokinetics QSAR QSPR Statistical learning methods Structure-activity relationship Toxicity Yap, C.W. Li, H. Ji, Z.L. Chen, Y.Z. Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
description	10.2174/138955707782331696
author2	PHARMACY
author_facet	PHARMACY Yap, C.W. Li, H. Ji, Z.L. Chen, Y.Z.
format	Article
author	Yap, C.W. Li, H. Ji, Z.L. Chen, Y.Z.
author_sort	Yap, C.W.
title	Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
title_short	Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
title_full	Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
title_fullStr	Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
title_full_unstemmed	Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
title_sort	regression methods for developing qsar and qspr models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties
publishDate	2014
url	http://scholarbank.nus.edu.sg/handle/10635/106296
_version_	1781788216021483520

Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties

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