[1. EU REACH Regulation Services [displayed 8 November 2011]. Available at http://www.intertek.com/reach/]Search in Google Scholar
[2. Tsakovska I, Worth A. The use of computational methods for the assessment of chemicals in REACH. Int J BIOautomation 2009;13:151-62.]Search in Google Scholar
[3. European Chemical Agency (ECHA). Guidance on information requirements and chemical safety assessment [displayed 30 April 2012]. Available at http://echa.europa.eu/guidance-documents/guidance-on-informationrequirements-and-chemical-safety-assessment]Search in Google Scholar
[4. Benfenati E, Diaza RG, Cassano A, Pardoe S, Gini G, Mays C, Knauf R, Benighaus L. The acceptance of in silico models for REACH: Requirements, barriers, and perspectives. Chem Cent J 2011;5:58-69.10.1186/1752-153X-5-58320189421982269]Search in Google Scholar
[5. Benfenati E, Gini G, Hoffmann S, Luttik R. Comparing invivo for chemical assessment: Problems and prospects. Altern Lab Anim 2010;38:153-66.10.1177/02611929100380020120507186]Search in Google Scholar
[6. Moudgal CJ, Young D, Nichols T, Martin T, Harten P, Venkatapathy R, Stelma G, Siddhanti S, Baier-Anderson C, Wolfe M. Application of QSARs and VFARs to the rapid risk assessment process at US EPA. SAR QSAR Environ Res 2008;19:579-87.10.1080/1062936080234894418853303]Search in Google Scholar
[7. Mezey PG, Carbo R, Girones X. Fundamentals of molecular similarity. New York: Kluwer Academic/ Plenum Publishers; 2001.]Search in Google Scholar
[8. Benfenati E. The CAESAR project for in silico models for the REACH legislation. Chem Cent J 2010;4(Suppl 1):I1.10.1186/1752-153X-4-S1-I1291332720678179]Search in Google Scholar
[9. Benfenati E, Benigni R, Demarini DM, Helma C, Kirkland D, Martin TM, Mazzatorta P, Ouedraogoarras G, Richard AM, Schilter B, Schoonen WGEJ, Snyder RD, Yang C. Predictive models for carcinogenicity and mutagenicity: Frameworks, state-of-the-art, and perspectives. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 2009;27:57-90.10.1080/1059050090288559319412856]Search in Google Scholar
[10. Organisation for Economic Co-operation and Development Guidance (OECD). Guidance document on the validation of (Q)SAR models Publications Series on Testing and Assessment No. 6 [displayed 5 July 2012]. Available at http://www.oecd.org/officialdocuments/displaydocumentpdf/?cote=env/jm/mono(2007)2&doclanguage=en]Search in Google Scholar
[11. Zarn JA, Bruschweiler BJ, Schlatter JR. Azole fungicides affect mammalian steroidogenesis by inhibiting sterol 14α- demethylase and aromatase. Environ Health Perspect 2003;111:255-61.10.1289/ehp.5785124138012611652]Search in Google Scholar
[12. Trosken ER, Fischer K, Volkel W, Lutz WK. Inhibition of human CYP19 by azoles used as antifungal agents and aromatase inhibitors, using a new LC-MS/MS method for the analysis of estradiol product formation. Toxicology 2006;219:33-40.10.1016/j.tox.2005.10.02016330141]Search in Google Scholar
[13. Bolčič-Tavčar M, Vračko M. Assessing the reproductive toxicity of some (con)azole compounds using Structure- Activity Relationship (SAR) approach. SAR QSAR Environ Res 2010;20:711-25.10.1080/1062936090343858620024805]Search in Google Scholar
[14. European Food Safety Authority (EFSA). PRAPeR publications [displayed 5 July 2012]. Available at http://www.efsa.europa.eu/en/supporting/pub/174e.htm]Search in Google Scholar
[15. Regulation (EC) No 1272/2008 of the European Parliament and of the Council of 16 December 2008 on classifi cation, labelling and packaging of substances and mixtures, amending and repealing Directives 67/548/EEC and 1999/45/ EC, and amending Regulation (EC) No 1907/2006 [displayed 5 July 2012]. Available at http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:353:0001:1355:en:PDF]Search in Google Scholar
[16. CAESAR project [displayed 8. November 2011]. Available at http://www.caesar-project.eu]Search in Google Scholar
[17. Ferrari T, Gini G. An open source multistep model to predict mutagenicity from statistical analysis and relevant structural alerts. Chem Centl J 2010;4(Suppl 1):S2.10.1186/1752-153X-4-S1-S2291332920678181]Search in Google Scholar
[18. Kazius J, McGuire R, Bursi R. Derivation and validation of toxicophores for mutagenicity prediction. J Med Chem 2005;48:312-20.10.1021/jm040835a15634026]Search in Google Scholar
[19. Fjodorova N, Vračko M, Novič M, Roncaglioni A, Benfenati E. New public QSAR model for carcinogenicity. Chem Cent J 2010;4(Suppl 1):S3.10.1186/1752-153X-4-S1-S3291333020678182]Search in Google Scholar
[20. Cassano A, Manganaro A, Martin T, Young D, Piclin N, Pintore M, Bigoni D, Benfenati E. CAESAR models for developmental toxicity. Chem Cent J 2010;4(Suppl 1):S4.10.1186/1752-153X-4-S1-S4291333120678183]Search in Google Scholar
[21. Arena VC, Sussman NB, Mazumdar S, Yu S, Macina OT. The utility of Structure-Activity Relationship (SAR) models for prediction and covariate selection in developmental toxicity: comparative analysis of logistic regression and decision tree models. SAR QSAR Environ Res 2004;15:1-18.10.1080/106293603200016963315113065]Search in Google Scholar
[22. Chaudhry Q, Piclin N, Cotterill J, Pintore M, Price NR, Cretien JR, Roncaglioni A. Global QSAR models for skin sensitisers for regulatory purposes. Chem Cent J 2010;4(Suppl 1):S5.10.1186/1752-153X-4-S1-S5291333220678184]Search in Google Scholar
[23. Gerberick GF, Ryan CA, Kern PS, Schaltter H, Dearman RJ, Kimber I, Patlewicz GY, Basketter DA. Compilation of historical local node data for evaluation of skin sensitization alternative methods. Dermatitis 2005;16:157-202.]Search in Google Scholar
[24. Bishop CM. Neural Networks for Pattern Recognition. Oxford: Oxford University Press; 1995.10.1201/9781420050646.ptb6]Search in Google Scholar