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Perspectives from the NanoSafety Modelling Cluster on the validation criteria for (Q)SAR models used in nanotechnology.
Puzyn T, Jeliazkova N, Sarimveis H, Marchese Robinson RL, Lobaskin V, Rallo R, Richarz AN, Gajewicz A, Papadopulos MG, Hastings J, Cronin MTD, Benfenati E, Fernández A. Puzyn T, et al. Among authors: benfenati e. Food Chem Toxicol. 2018 Feb;112:478-494. doi: 10.1016/j.fct.2017.09.037. Epub 2017 Sep 21. Food Chem Toxicol. 2018. PMID: 28943385 Free article.
Identification of the structural requirements of the receptor-binding affinity of diphenolic azoles to estrogen receptors alpha and beta by three-dimensional quantitative structure-activity relationship and structure-activity relationship analysis.
Demyttenaere-Kovatcheva A, Cronin MT, Benfenati E, Roncaglioni A, Lopiparo E. Demyttenaere-Kovatcheva A, et al. Among authors: benfenati e. J Med Chem. 2005 Dec 1;48(24):7628-36. doi: 10.1021/jm050604j. J Med Chem. 2005. PMID: 16302803
Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study.
Vracko M, Bandelj V, Barbieri P, Benfenati E, Chaudhry Q, Cronin M, Devillers J, Gallegos A, Gini G, Gramatica P, Helma C, Mazzatorta P, Neagu D, Netzeva T, Pavan M, Patlewicz G, Randić M, Tsakovska I, Worth A. Vracko M, et al. Among authors: benfenati e. SAR QSAR Environ Res. 2006 Jun;17(3):265-84. doi: 10.1080/10659360600787650. SAR QSAR Environ Res. 2006. PMID: 16815767
Predictive models for carcinogenicity and mutagenicity: frameworks, state-of-the-art, and perspectives.
Benfenati E, Benigni R, Demarini DM, Helma C, Kirkland D, Martin TM, Mazzatorta P, Ouédraogo-Arras G, Richard AM, Schilter B, Schoonen WG, Snyder RD, Yang C. Benfenati E, et al. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2009 Apr;27(2):57-90. doi: 10.1080/10590500902885593. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2009. PMID: 19412856 Review.
391 results