D. J. Aldous, Exchangeability and related topics, ´ Ecole d'´ eté de probabilités de Saint Flour XIII, Lecture Notes in Mathematics, vol.1117, 1985.

Y. Baraud, Non-asymptotic rates of testing in signal detection, Bernoulli, vol.8, issue.5, pp.577-606, 2002.

Y. Baraud, S. Huet, and B. Laurent, Adaptative tests of linear hypotheses by model selection, Ann. Statist, vol.31, issue.1, pp.225-251, 2003.

P. Bühlmann, M. Kalisch, and . Zürich, Variable selection for high-dimensional models: partial faithful distributions, strong assocations and the PC-algorithm, 2008.

E. Candès and T. Tao, The Dantzig selector: Statistical estimation when p is much larger than n, The Annals of Statistics, vol.35, issue.6, pp.2313-2351, 2007.
DOI : 10.1214/009053606000001523

N. Cressie, Statistics for Spatial Data, Revised Edition., Biometrics, vol.50, issue.1, 1993.
DOI : 10.2307/2533238

M. Drton and M. Perlman, Multiple Testing and Error Control in Gaussian Graphical Model Selection, Statistical Science, vol.22, issue.3, pp.430-449, 2007.
DOI : 10.1214/088342307000000113

B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, Least angle regression, Ann. Statist, vol.32, issue.2, pp.407-499, 2004.

C. Giraud, Estimation of Gaussian graphs by model selection, arxiv:math.ST/0710, 2008.

J. Huang, N. Liu, M. Pourahmadi, and L. Liu, Covariance matrix selection and estimation via penalised normal likelihood, Biometrika, vol.93, issue.1, pp.85-98, 2006.
DOI : 10.1093/biomet/93.1.85

Y. I. Ingster, Asymptotically minimax hypothesis testing for nonparametric alternatives I, Math. Methods Statist, vol.2, pp.85-114, 1993.

Y. I. Ingster, Asymptotically minimax hypothesis testing for nonparametric alternatives II, Math. Methods Statist, vol.3, pp.171-189, 1993.

Y. I. Ingster, Asymptotically minimax hypothesis testing for nonparametric alternatives III, Math. Methods Statist, vol.4, pp.249-268, 1993.

H. Kishino and P. Waddell, Correspondence analysis of genes and tissue types and finding genetic links from microarray data, Genome Informatics, vol.11, pp.83-95, 2000.

B. Laurent and P. Massart, Adaptive estimation of a quadratic function by model selection, Ann. of Statist, vol.28, issue.5, pp.1302-1338, 2000.

S. L. Lauritzen, Graphical Models, 1996.

P. Massart, Concentration Inequalities and Model Selection, ´ Ecole d'´ eté de probabilités de Saint Flour XXXIII, Lecture Notes in Mathematics, vol.1896, 2007.

N. Meinshausen and P. Bühlmann, High-dimensional graphs and variable selection with the Lasso, The Annals of Statistics, vol.34, issue.3, pp.1436-1462, 2006.
DOI : 10.1214/009053606000000281

H. Rue and L. Held, Gaussian Markov Random Fields: Theory and Applications, 2005.
DOI : 10.1201/9780203492024

J. Schäfer and K. Strimmer, An empirical Bayes approach to inferring large-scale gene association networks, Bioinformatics, vol.21, issue.6, pp.754-764, 2005.
DOI : 10.1093/bioinformatics/bti062

V. G. Spokoiny, Adaptative hypothesis testing using wavelets, Ann. Statist, vol.24, pp.2477-2498, 1996.

N. Verzelen and F. Villers, Tests for Gaussian graphical models, Computational Statistics & Data Analysis, vol.53, issue.5, p.193268, 2007.
DOI : 10.1016/j.csda.2008.09.022

URL : https://hal.archives-ouvertes.fr/hal-00193268

M. J. Wainwright, Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting, IEEE Transactions on Information Theory, vol.55, issue.12, 2007.
DOI : 10.1109/TIT.2009.2032816

A. Wille and P. Bühlmann, Low-Order Conditional Independence Graphs for Inferring Genetic Networks, Statistical Applications in Genetics and Molecular Biology, vol.5, issue.1, 2006.
DOI : 10.2202/1544-6115.1170

M. Yuan and Y. Lin, Model selection and estimation in the Gaussian graphical model, Biometrika, vol.94, issue.1, pp.19-35, 2007.
DOI : 10.1093/biomet/asm018

C. Zhang and J. Huang, The sparsity and bias of the Lasso selection in high-dimensional linear regression, The Annals of Statistics, vol.36, issue.4, 2008.
DOI : 10.1214/07-AOS520

P. Zhao and B. Yu, On model selection consistency of Lasso, J. Mach. Learn. Res, vol.7, pp.2541-2563, 2006.

H. Zou and T. Hastie, Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005.
DOI : 10.1073/pnas.201162998

I. Unité-de-recherche, . Lorraine, . Loria, and . Technopôle-de-nancy, Brabois -Campus scientifique 615, rue du Jardin Botanique -BP 101 -54602 Villers-lès-Nancy Cedex (France) Unité de recherche INRIA Rennes : IRISA, Campus universitaire de Beaulieu -35042 Rennes Cedex (France) Unité de recherche INRIA Rhône-Alpes : 655, avenue de l'Europe -38334 Montbonnot Saint-Ismier (France) Unité de recherche INRIA Rocquencourt, Domaine de Voluceau -Rocquencourt -BP 105 -78153 Le Chesnay Cedex (France) Unité de recherche INRIA Sophia Antipolis : 2004, route des Lucioles -BP 93 -06902 Sophia Antipolis Cedex