Gramatica P - Search Results

1

QSAR study of malonyl-CoA decarboxylase inhibitors using GA-MLR and a new strategy of consensus modeling.

Li J, Lei B, Liu H, Li S, Yao X, Liu M, Gramatica P. Li J, et al. Among authors: gramatica p. J Comput Chem. 2008 Dec;29(16):2636-47. doi: 10.1002/jcc.21002. J Comput Chem. 2008. PMID: 18484640

2

Statistical external validation and consensus modeling: a QSPR case study for Koc prediction.

Gramatica P, Giani E, Papa E. Gramatica P, et al. J Mol Graph Model. 2007 Mar;25(6):755-66. doi: 10.1016/j.jmgm.2006.06.005. Epub 2006 Aug 4. J Mol Graph Model. 2007. PMID: 16890002

3

QSAR prediction of estrogen activity for a large set of diverse chemicals under the guidance of OECD principles.

Liu H, Papa E, Gramatica P. Liu H, et al. Among authors: gramatica p. Chem Res Toxicol. 2006 Nov;19(11):1540-8. doi: 10.1021/tx0601509. Chem Res Toxicol. 2006. PMID: 17112243

4

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

Liu H, Papa E, Walker JD, Gramatica P. Liu H, et al. Among authors: gramatica p. J Mol Graph Model. 2007 Jul;26(1):135-44. doi: 10.1016/j.jmgm.2007.01.003. Epub 2007 Jan 17. J Mol Graph Model. 2007. PMID: 17293141

5

QSAR study of selective ligands for the thyroid hormone receptor beta.

Liu H, Gramatica P. Liu H, et al. Among authors: gramatica p. Bioorg Med Chem. 2007 Aug 1;15(15):5251-61. doi: 10.1016/j.bmc.2007.05.016. Epub 2007 May 10. Bioorg Med Chem. 2007. PMID: 17524652

6

Evaluation and QSAR modeling on multiple endpoints of estrogen activity based on different bioassays.

Liu H, Papa E, Gramatica P. Liu H, et al. Among authors: gramatica p. Chemosphere. 2008 Feb;70(10):1889-97. doi: 10.1016/j.chemosphere.2007.07.071. Epub 2007 Sep 19. Chemosphere. 2008. PMID: 17884132

7

Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis.

Zhu H, Tropsha A, Fourches D, Varnek A, Papa E, Gramatica P, Oberg T, Dao P, Cherkasov A, Tetko IV. Zhu H, et al. Among authors: gramatica p. J Chem Inf Model. 2008 Apr;48(4):766-84. doi: 10.1021/ci700443v. Epub 2008 Mar 1. J Chem Inf Model. 2008. PMID: 18311912 Free article.

8

The applications of machine learning algorithms in the modeling of estrogen-like chemicals.

Liu H, Yao X, Gramatica P. Liu H, et al. Among authors: gramatica p. Comb Chem High Throughput Screen. 2009 Jun;12(5):490-6. doi: 10.2174/138620709788489037. Comb Chem High Throughput Screen. 2009. PMID: 19519328

9

A new strategy to improve the predictive ability of the local lazy regression and its application to the QSAR study of melanin-concentrating hormone receptor 1 antagonists.

Li J, Li S, Lei B, Liu H, Yao X, Liu M, Gramatica P. Li J, et al. Among authors: gramatica p. J Comput Chem. 2010 Apr 15;31(5):973-85. doi: 10.1002/jcc.21383. J Comput Chem. 2010. PMID: 19670228

10

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. Li J, et al. Among authors: gramatica p. Mol Divers. 2010 Nov;14(4):687-96. doi: 10.1007/s11030-009-9212-2. Epub 2009 Nov 17. Mol Divers. 2010. PMID: 19921452

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