X. Chen, X. Shi, X. Xu, Z. Wang, R. Mills et al., A two-graph guided multi-task lasso approach for eqtl mapping, International Conference on Artificial Intelligence and Statistics (AISTATS), 2012, pp.208-217, 2012.

W. S. Cleveland, LOWESS: A Program for Smoothing Scatterplots by Robust Locally Weighted Regression, The American Statistician, vol.35, issue.1, pp.829-836, 1981.
DOI : 10.2307/2683591

N. C. Gordon, J. R. Price, K. Cole, R. A. Everitt, F. Finney et al., Prediction of Staphylococcus aureus Antimicrobial Resistance by Whole-Genome Sequencing, Journal of Clinical Microbiology, vol.52, issue.4, pp.1182-1191, 2014.
DOI : 10.1128/JCM.03117-13

R. Jenatton and J. Mairal, Proximal methods for sparse hierarchical dictionary learning, International Conference on Machine Learning, 2010.

R. Jenatton, J. Mairal, G. Obozinski, and F. Bach, Proximal methods for hierarchical sparse coding, J. Mach. Learn. Res, vol.12, pp.2297-2334, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00516723

S. Kim and E. P. Xing, Tree-guided group lasso for multi-task regression with structured sparsity, International Conference on Machine Learning, pp.543-550, 2010.
DOI : 10.1214/12-aoas549
URL : http://arxiv.org/abs/0909.1373

V. N. Kos, M. Déraspe, R. E. Mclaughlin, J. D. Whiteaker, P. H. Roy et al., The Resistome of Pseudomonas aeruginosa in Relationship to Phenotypic Susceptibility, Antimicrobial Agents and Chemotherapy, vol.59, issue.1, pp.427-436, 2015.
DOI : 10.1128/AAC.03954-14

S. Lee and E. Xing, Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs, Bioinformatics, vol.28, issue.12, pp.137-146, 2012.
DOI : 10.1093/bioinformatics/bts227

P. Machart, L. Baldassarre, and S. Anthoine, Optimal Computational Trade-Off of Inexact Proximal Methods, Multi-Trade-offs Mach. Learn, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00771722

J. Mairal, R. Jenatton, G. Obozinski, and F. Bach, Convex and network flow optimization for structured sparsity, J. Mach. Learn. Res, vol.12, pp.2681-2720, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00584817

G. Obozinski, M. J. Wainwright, and M. I. Jordan, High-dimensional support union recovery in multivariate regression, Advances in Neural Information Processing Systems, pp.1217-1224, 2008.
DOI : 10.1109/allerton.2008.4797530
URL : http://arxiv.org/pdf/0808.0711v1.pdf

K. B. Petersen, M. S. Pedersen, J. Larsen, K. Strimmer, L. Christiansen et al., The matrix cookbook, 2006.

M. Schmidt, N. L. Roux, and F. Bach, Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization, In Adv. Neural Inf. Process. Syst, issue.2, pp.1-9, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00618152

J. A. Tropp, Algorithms for simultaneous sparse approximation. Part II: Convex relaxation, Signal Processing, vol.86, issue.3, pp.589-602, 2006.
DOI : 10.1016/j.sigpro.2005.05.031

P. Zhao, G. Rocha, and B. Yu, The composite absolute penalties family for grouped and hierarchical variable selection. The Annals of Statistics, pp.3468-3497, 2009.