S. Arlot and P. Massart, Data-driven calibration of penalties for leastsquares regression, Journal of Machine Learning Research, vol.10, pp.245-279, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00287631

L. Birgé and P. Massart, Minimal penalties for Gaussian model selection. Probability Theory and Related Fields, pp.33-73, 2007.

C. Chen, F. Forbes, and O. Francois, fastruct: model-based clustering made faster, Molecular Ecology Notes, vol.58, issue.4, pp.980-983, 2006.
DOI : 10.1111/j.1471-8286.2006.01527.x

J. Corander, P. Marttinen, J. Sirén, and J. Tang, Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations, BMC Bioinformatics, vol.9, issue.1, p.539, 2002.
DOI : 10.1186/1471-2105-9-539

P. Massart, Concentration inequalities and model selection, Lecture Notes in Mathematics, vol.1896, 2007.

C. Maugis and B. Michel, A non asymptotic penalized criterion for Gaussian mixture model selection, ESAIM: Probability and Statistics, vol.15, 2009.
DOI : 10.1051/ps/2009004
URL : https://hal.archives-ouvertes.fr/inria-00284613

J. Pritchard, M. Stephens, and P. Donnelly, Inference of population structure using multilocus genotype data, Genetics, vol.155, issue.2, pp.945-59, 2000.

W. Toussile and E. Gassiat, Variable selection in model-based clustering using multilocus genotype data Advances in Data Analysis and Classification, pp.109-134, 2009.

N. Verzelen, Adaptative estimation to regular Gaussian Markov random fields, 2009.

F. Villers, Tests et selection de modèles pour l'analyse de données protéomiques et transcriptomiques, 2007.