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SAR and QSAR in Environmental Research Volume 8, 1998 - Issue 3-4
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Original Articles

Using Recursive Partitioning to Analyze a Large Sar Data Set

S. S. Young Research Information Resources, Glaxo Wellcome Inc., Research Triangle Park, NC, 27709, USA
&
D. M. Hawkins Department of Applied Statistics, University of Minnesota, St. Paul, MN, 55108, USA
Pages 183-193 | Received 22 Mar 1997, Accepted 03 May 1997, Published online: 05 Oct 2006

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J. Devillers, A. Doucet-Panaye & J.P. Doucet. (2015) Structure–activity relationship (SAR) modelling of mosquito larvicides. SAR and QSAR in Environmental Research 26:4, pages 263-278.
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J. Devillers, C. Lagneau, A. Lattes, J.C. Garrigues, M.M. Clémenté & A. Yébakima. (2014) In silico models for predicting vector control chemicals targeting Aedes aegypti. SAR and QSAR in Environmental Research 25:10, pages 805-835.
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S. C. Basak, R. Natarajan, D. Mills, D. M. Hawkins & J. J. Kraker. (2005) Quantitative structure-activity relationship modeling of insect juvenile hormone activity of 2,4-dienoates using computed molecular descriptors. SAR and QSAR in Environmental Research 16:6, pages 581-606.
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Raghavan Sampathkumar, Joel Scott-Herridge, Binhua Liang, Joshua Kimani, Francis Plummer & Ma Luo. (2017) HIV-1 Subtypes and 5’LTR-Leader Sequence Variants Correlate with Seroconversion Status in Pumwani Sex Worker Cohort. Viruses 10:1, pages 4.
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Sheng Tian, Junmei Wang, Youyong Li, Dan Li, Lei Xu & Tingjun Hou. (2015) The application of in silico drug-likeness predictions in pharmaceutical research. Advanced Drug Delivery Reviews 86, pages 2-10.
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Jabed H. Tomal, William J. Welch & Ruben H. Zamar. (2015) Ensembling classification models based on phalanxes of variables with applications in drug discovery. The Annals of Applied Statistics 9:1.
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. 2013. Juvenile Hormones and Juvenoids. Juvenile Hormones and Juvenoids 145 174 .
Y.C. Martin. 2013. Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Reference Module in Chemistry, Molecular Sciences and Chemical Engineering.
Yan Yuan, Hugh A. Chipman & William J. Welch. (2012) Harvesting Classification Trees for Drug Discovery. Journal of Chemical Information and Modeling 52:12, pages 3169-3180.
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Sheng Tian, Junmei Wang, Youyong Li, Xiaojie Xu & Tingjun Hou. (2012) Drug-likeness Analysis of Traditional Chinese Medicines: Prediction of Drug-likeness Using Machine Learning Approaches. Molecular Pharmaceutics 9:10, pages 2875-2886.
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Steven L. Dixon. 2010. Drug Design. Drug Design 137 150 .
Roberto Todeschini & Viviana Consonni. 2009. Molecular Descriptors for Chemoinformatics. Molecular Descriptors for Chemoinformatics 1 241 .
Christian Kramer, Bernd Beck, Jan M. Kriegl & Timothy Clark. (2008) A Composite Model for hERG Blockade. ChemMedChem 3:2, pages 254-265.
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Y.C. Martin. 2007. Comprehensive Medicinal Chemistry II. Comprehensive Medicinal Chemistry II 119 147 .
Donald J. AbrahamA. Tropsha. 2003. Burger's Medicinal Chemistry and Drug Discovery. Burger's Medicinal Chemistry and Drug Discovery 49 76 .
Roberto Todeschini & Viviana Consonni. 2000. Handbook of Molecular Descriptors. Handbook of Molecular Descriptors 524 667 .
Sung Jin Cho, C. Frank Shen & Mark A. Hermsmeier. (2000) Binary Formal Inference-Based Recursive Modeling Using Multiple Atom and Physicochemical Property Class Pair and Torsion Descriptors as Decision Criteria. Journal of Chemical Information and Computer Sciences 40:3, pages 668-680.
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Deborah K. Jones-Hertzog, Pabak Mukhopadhyay, Christopher E. Keefer & S.Stanley Young. (1999) Use of recursive partitioning in the sequential screening of G-protein–coupled receptors. Journal of Pharmacological and Toxicological Methods 42:4, pages 207-215.
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Xin Chen, Rusinko, Alexandler Tropsha & S. Stanley Young. (1999) Automated Pharmacophore Identification for Large Chemical Data Sets. Journal of Chemical Information and Computer Sciences 39:5, pages 887-896.
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Xin Chen, Andrew Rusinko & S. Stanley Young. (1998) Recursive Partitioning Analysis of a Large Structure−Activity Data Set Using Three-Dimensional Descriptors. Journal of Chemical Information and Computer Sciences 38:6, pages 1054-1062.
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