Advanced search
Publication Cover
SAR and QSAR in Environmental Research Volume 19, 2008 - Issue 1-2
Submit an article Journal homepage
143
Views
17
CrossRef citations to date
0
Altmetric
Original Articles

Decision trees versus support vector machine for classification of androgen receptor ligandsFootnote1

A. Panaye ITODYS, Université Paris 7 Denis Diderot, UMR7086 CNRS, Paris, FranceCorrespondence[email protected]
,
J.P. Doucet ITODYS, Université Paris 7 Denis Diderot, UMR7086 CNRS, Paris, France
,
J. Devillers CTIS, Rillieux la Pape, France
,
N. Marchand-Geneste Université de Bordeaux I, CNRS UMR5255, ISM-LPTC, Talence Cedex, France
&
J.M. Porcher INERIS, Parc Technologique ALATA, Verneuil en Halatte, France
Pages 129-151 | Received 05 Sep 2007, Accepted 28 Nov 2007, Published online: 04 Dec 2010

References

  • United States Environmental Protection Agency. 1998 . Endocrine Disruptor Screening and Testing Advisory Committee (EDSTAC) Final Report Retrieved Nov 27, 2004 from the website: http://www.epa.gov/scipoly/oscpendo/edspoverview/finalrpt.htm
  • Hong , H . 2003 . Comparative molecular field analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor . SAR QSAR Environ. Res. , 14 : 373 – 388 .
  • Waller , CL . 1996 . Three-dimensional quantitative structure-activity relationships for androgen receptor ligands . Toxicol. Appl. Pharmacol. , 137 : 219 – 227 .
  • Burden , PM . 2000 . Chiral derivatives of 2-cyclohexylideneperhydro-4,7-methanoindenes, a novel class of nonsteroidal androgen receptor ligand: synthesis, X-ray analysis and biological activity . J. Med. Chem. , 43 : 4629 – 4635 .
  • Bohl , CE . 2004 . Ligand-based approach to identify quantitative structure activity relationships for the androgen receptor, J. Med. Chem. , 47 : 3765 – 3776 .
  • Tamura , H . 2006 . Structural basis for androgen receptor agonists and antagonists: Interaction of SPEED 98-listed chemicals and related compounds with the androgen receptor based on an in vitro reporter gene assay and 3D-QSAR . Biorg. Med. Chem. , 14 : 7160 – 7174 .
  • Lill , MA . 2005 . Impact of induced fit on ligand binding to the androgen receptor: a multidimensional QSAR study to predict endocrine-disrupting effects of environmental chemicals . J. Med. Chem. , 48 : 5666 – 5674 .
  • Söderholm , AA , Lehtovuori , PT and Nyrönen , TH . 2005 . Three-dimensional structure-activity relationships of nonsteroidal ligands in complex with androgen receptor ligand-binding domain . J. Med. Chem. , 48 : 917 – 925 .
  • Zhao , CY . 2005 . QSAR study of natural, synthetic and environmental endocrine disrupting compounds for binding to the androgen receptor . SAR QSAR Environ. Res. , 16 : 349 – 367 .
  • Loughney , DA and Schwender , CF . 1992 . A comparison of progestin and androgen receptor binding using the CoMFA technique . J. Comput. -Aided Mol. Des. , 6 : 569 – 581 .
  • Marhefka , CA . 2001 . Homology modeling using multiple molecular dynamics simulations and docking studies of the human androgen receptor ligand binding domain bound to testosterone and nonsteroidal ligands . J. Med. Chem. , 44 : 1729 – 1740 .
  • Karabunarliev , S . 2003 . Rule interpreter: a chemical language for structure-based screening . J. Mol. Struct. (Theochem) , 622 : 53 – 62 .
  • Serafimova , R , Walker , J and Mekenyan , O . 2002 . Androgen receptor binding affinity of pesticide “active” formulation ingredients. QSAR evaluation by COREPA method . SAR QSAR Environ. Res. , 13 : 127 – 134 .
  • Fang , H . 2003 . Study of 202 natural, synthetic and environmental chemicals for binding to the androgen receptor . Chem. Res. Toxicol. , 16 : 1338 – 1358 .
  • Devillers , J . 2007 . “ European SETAC 2007 Meeting ” . In Linear vs. nonlinear QSAR models for androgen receptor binding affinity of natural and man-made chemicals , Portugal : Porto .
  • Cliff , N . 1987 . Analyzing Multivariate Data , San Diego : Harcourt Brace Javanovich Publishers .
  • Breiman , L . 1984 . Classification and Regression Trees , Boca Raton : Chapman and Hall .
  • Vapnik , VN . 1995 . The Nature of Statistical Learning Theory , Berlin : Springer .
  • Cortes , C and Vapnik , V . 1995 . Support vector networks . Machine Learning , 20 : 273 – 297 .
  • Doucet , JP . Non linear SVM approaches to QSPR/QSAR studies and Drug Design . Cur. Comput. -Aided Drug Des. , In Press
  • Devillers , J . 1996 . Neural Networks in QSAR and Drug Design , London : Academic Press .
  • Katrizky , AR , Lobanov , VS and Karelson , M . 1995 . CODESSA, Reference manual , Gainesville : University of Florida .
  • team , R Development Core . 2007 . R: A language and environment for statistical computing. R Foundation for Statistical Computing Vienna, , Austria ISBN 3-900051-07-0, URL http://www.R-project.org.
  • Dimitriadou , E . e1071: Misc Functions of the Department of Statistics . TU Wien. R package version 1.5–16

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.