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Items: 1 to 20 of 246

1.
2.

Quantitative structure-activity relationship models for prediction of estrogen receptor binding affinity of structurally diverse chemicals.

Schmieder PK, Ankley G, Mekenyan O, Walker JD, Bradbury S.

Environ Toxicol Chem. 2003 Aug;22(8):1844-54. Review.

PMID:
12924583
3.

Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

Ng HW, Doughty SW, Luo H, Ye H, Ge W, Tong W, Hong H.

Chem Res Toxicol. 2015 Dec 21;28(12):2343-51. doi: 10.1021/acs.chemrestox.5b00358. Epub 2015 Nov 12.

PMID:
26524122
4.

Performance of (consensus) kNN QSAR for predicting estrogenic activity in a large diverse set of organic compounds.

Asikainen AH, Ruuskanen J, Tuppurainen KA.

SAR QSAR Environ Res. 2004 Feb;15(1):19-32. Review.

PMID:
15113066
5.

Conformal Prediction Classification of a Large Data Set of Environmental Chemicals from ToxCast and Tox21 Estrogen Receptor Assays.

Norinder U, Boyer S.

Chem Res Toxicol. 2016 Jun 20;29(6):1003-10. doi: 10.1021/acs.chemrestox.6b00037. Epub 2016 May 13.

PMID:
27152554
6.

The importance of molecular structures, endpoints' values, and predictivity parameters in QSAR research: QSAR analysis of a series of estrogen receptor binders.

Li J, Gramatica P.

Mol Divers. 2010 Nov;14(4):687-96. doi: 10.1007/s11030-009-9212-2. Epub 2009 Nov 17.

PMID:
19921452
8.

Binary classification of a large collection of environmental chemicals from estrogen receptor assays by quantitative structure-activity relationship and machine learning methods.

Zang Q, Rotroff DM, Judson RS.

J Chem Inf Model. 2013 Dec 23;53(12):3244-61. doi: 10.1021/ci400527b. Epub 2013 Dec 11.

PMID:
24279462
9.

QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes.

Basant N, Gupta S.

Environ Sci Pollut Res Int. 2017 Jun;24(16):14430-14444. doi: 10.1007/s11356-017-8903-y. Epub 2017 Apr 24.

PMID:
28435990
10.
11.

In silico screening of estrogen-like chemicals based on different nonlinear classification models.

Liu H, Papa E, Walker JD, Gramatica P.

J Mol Graph Model. 2007 Jul;26(1):135-44. Epub 2007 Jan 17.

PMID:
17293141
12.

Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts.

Hong H, Tong W, Fang H, Shi L, Xie Q, Wu J, Perkins R, Walker JD, Branham W, Sheehan DM.

Environ Health Perspect. 2002 Jan;110(1):29-36.

13.

Rank order entropy: why one metric is not enough.

McLellan MR, Ryan MD, Breneman CM.

J Chem Inf Model. 2011 Sep 26;51(9):2302-19. doi: 10.1021/ci200170k. Epub 2011 Aug 29.

14.

Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling.

Valerio LG Jr, Arvidson KB, Chanderbhan RF, Contrera JF.

Toxicol Appl Pharmacol. 2007 Jul 1;222(1):1-16. Epub 2007 Mar 24.

PMID:
17482223
15.

QSAR models using a large diverse set of estrogens.

Shi LM, Fang H, Tong W, Wu J, Perkins R, Blair RM, Branham WS, Dial SL, Moland CL, Sheehan DM.

J Chem Inf Comput Sci. 2001 Jan-Feb;41(1):186-95.

PMID:
11206373
16.

A comparison of model performance for six quantitative structure-activity relationship packages that predict acute toxicity to fish.

Moore DR, Breton RL, MacDonald DB.

Environ Toxicol Chem. 2003 Aug;22(8):1799-809. Review.

PMID:
12924579
17.

Critical assessment of QSAR models of environmental toxicity against Tetrahymena pyriformis: focusing on applicability domain and overfitting by variable selection.

Tetko IV, Sushko I, Pandey AK, Zhu H, Tropsha A, Papa E, Oberg T, Todeschini R, Fourches D, Varnek A.

J Chem Inf Model. 2008 Sep;48(9):1733-46. doi: 10.1021/ci800151m. Epub 2008 Aug 26.

PMID:
18729318
18.

Multispecies QSAR modeling for predicting the aquatic toxicity of diverse organic chemicals for regulatory toxicology.

Singh KP, Gupta S, Kumar A, Mohan D.

Chem Res Toxicol. 2014 May 19;27(5):741-53. doi: 10.1021/tx400371w. Epub 2014 Apr 17.

PMID:
24738471
20.

Binary classification models for endocrine disrupter effects mediated through the estrogen receptor.

Roncaglioni A, Piclin N, Pintore M, Benfenati E.

SAR QSAR Environ Res. 2008;19(7-8):697-733. doi: 10.1080/10629360802550606.

PMID:
19061085

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