T. I. Netzeva, Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52, Altern Lab Anim, vol.33, issue.2, pp.155-73, 2005.

H. Dragos, M. Gilles, and V. Alexandre, Predicting the Predictability: A Unified Approach to the Applicability Domain Problem of QSAR Models, Journal of Chemical Information and Modeling, vol.49, issue.7, pp.1762-76, 2009.
DOI : 10.1021/ci9000579

J. Jaworska, S. Gabbert, and T. Aldenberg, Towards optimization of chemical testing under REACH: A Bayesian network approach to Integrated Testing Strategies, Regulatory Toxicology and Pharmacology, vol.57, issue.2-3, pp.157-67, 2010.
DOI : 10.1016/j.yrtph.2010.02.003

A. Bassan and A. P. Worth, Computational Tools for Regulatory Needs, pp.751-775, 2007.
DOI : 10.1002/9780470145890.ch27

URL : http://publications.jrc.ec.europa.eu/repository/handle/JRC37871

V. Vovk, A. Gammerman, and G. Shafer, Algorithmic Learning in a Random World, 2005.

G. Shafer and V. Vovk, A Tutorial on Conformal Prediction, Journal of Machine Learning Research, vol.9, pp.371-421, 2008.

T. A. Halgren, Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94, Journal of Computational Chemistry, vol.92, issue.5-6, pp.5-6, 1996.
DOI : 10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P

Z. Bosni´cbosni´c and I. Kononenko, Comparison of approaches for estimating reliability of individual regression predictions, Data & Knowledge Engineering, vol.67, issue.3, pp.504-516, 2008.
DOI : 10.1016/j.datak.2008.08.001

J. L. Faulon, . Visco, D. P. Jr, and R. S. Pophale, The Signature Molecular Descriptor. 1. Using Extended Valence Sequences in QSAR and QSPR Studies, Journal of Chemical Information and Computer Sciences, vol.43, issue.3, pp.707-727, 2003.
DOI : 10.1021/ci020345w

J. L. Faulon, M. J. Collins, and R. D. Carr, The Signature Molecular Descriptor. 4. Canonizing Molecules Using Extended Valence Sequences, Journal of Chemical Information and Computer Sciences, vol.44, issue.2, pp.427-463, 2004.
DOI : 10.1021/ci0341823

V. N. Vapnik, Statistical learning theory. 1 edn, 1998.

C. C. Chang and C. J. Lin, LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.1-2727, 2011.
DOI : 10.1145/1961189.1961199

H. Papadopoulos, V. Vovk, and A. Gammerman, Regression conformal prediction with nearest neighbours, J. Artif. Int. Res, vol.40, issue.1, pp.815-840, 2011.

J. Huuskonen, Estimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology, Journal of Chemical Information and Computer Sciences, vol.40, issue.3, pp.773-777, 2000.
DOI : 10.1021/ci9901338

J. L. Hintze and R. D. Nelson, Violin plots: A box plot-density trace synergism, The American Statistician, vol.52, issue.2, pp.181-84, 1998.
DOI : 10.2307/2685478

D. Adler, vioplot: Violin plot, 2005.

J. H. Van-drie, Pharmacophore Discovery - Lessons Learned, Current Pharmaceutical Design, vol.9, issue.20, pp.1649-64, 2003.
DOI : 10.2174/1381612033454568