Population-Based in Vitro Hazard and Concentration???Response Assessment of Chemicals: The 1000 Genomes High-Throughput Screening Study, Environmental Health Perspectives, vol.123, issue.5, pp.458-466, 2015. ,
DOI : 10.1289/ehp.1408775
A map of human genome variation from population-scale sequencing, Nature, vol.467, issue.7319, pp.1061-73, 2010. ,
Genome-wide pharmacogenomic study of citalopram-induced side effects in STAR*D. Translational psychiatry, p.129, 2012. ,
A method and server for predicting damaging missense mutations, Nature methods, vol.7, issue.4, pp.248-257, 2010. ,
Deep learning for computational biology, Molecular Systems Biology, vol.12, issue.7, p.878, 2016. ,
DOI : 10.15252/msb.20156651
Genome-wide association study of 107 phenotypes in a common set of Arabidopsis thaliana inbred lines, Nature, issue.7298, pp.465627-631, 2010. ,
URL : https://hal.archives-ouvertes.fr/hal-00468440
Efficient network-guided multi- 122 BIBLIOGRAPHY locus association mapping with graph cuts, Bioinformatics, issue.13, pp.29-171, 2013. ,
DOI : 10.1093/bioinformatics/btt238
URL : https://academic.oup.com/bioinformatics/article-pdf/29/13/i171/18536066/btt238.pdf
Task Clustering and Gating for Bayesian Multitask Learning, Journal of Machine Learning Research, vol.4, issue.1, pp.83-99, 2003. ,
MULTITASK FEATURE SELECTION WITH TASK DESCRIPTORS, Biocomputing 2016, pp.261-272, 2016. ,
DOI : 10.1142/9789814749411_0025
URL : https://hal.archives-ouvertes.fr/hal-01246697
Kernel methods for predicting protein-protein interactions, Bioinformatics, vol.21, issue.Suppl 1, 2005. ,
DOI : 10.1093/bioinformatics/bti1016
URL : https://academic.oup.com/bioinformatics/article-pdf/21/suppl_1/i38/524723/bti1016.pdf
Kernel bilinear regression for toxicogenetics, RECOMB Conference on Regulatory and Systems Genomics, 2013. ,
DOI : 10.1002/minf.201700053
URL : http://onlinelibrary.wiley.com/doi/10.1002/minf.201700053/pdf
Multi-task learning for HIV therapy screening, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.56-63, 2008. ,
DOI : 10.1145/1390156.1390164
URL : http://icml2008.cs.helsinki.fi/papers/520.pdf
Kernel multi-task learning using task-specific features, The 11th International Conference on Artificial Intelligence and Statistics, pp.43-50, 2007. ,
Multi-task Gaussian process prediction, Advances in Neural Information Processing Systems, pp.153-160, 2007. ,
Random forests, Machine learning, pp.5-32, 2001. ,
Better Subset Regression Using the Nonnegative Garrote, Technometrics, vol.37, issue.4, pp.373-384, 1995. ,
DOI : 10.1080/01621459.1980.10477428
Classification and regression trees, 1984. ,
Predicting Adverse Drug Events Using Pharmacological Network Models, Science Translational Medicine, vol.7, issue.11, 2011. ,
DOI : 10.1016/S1359-6446(02)02288-2
Kernel methods: a survey of current techniques, Neurocomputing, vol.48, issue.1-4, pp.63-84, 2002. ,
DOI : 10.1016/S0925-2312(01)00643-9
The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases, Nucleic Acids Research, vol.60, issue.D1, pp.471-480, 2015. ,
DOI : 10.1093/bioinformatics/btt291
In vitro methods in pharmaceutical research Academic press, 1996. ,
Bridging the gap between in vitro and in vivo: Dose and schedule predictions for the ATR inhibitor AZD6738, Scientific Reports, vol.28, issue.1, 2015. ,
DOI : 10.1093/bioinformatics/bts288
Predicting Drugs Side Effects Based on Chemical-Chemical Interactions and Protein-Chemical Interactions, BioMed Research International, vol.8, issue.4, p.485034, 2013. ,
DOI : 10.1586/epr.11.20
URL : http://doi.org/10.1155/2013/485034
Predicting Drugs Side Effects Based on Chemical-Chemical Interactions and Protein-Chemical Interactions, BioMed Research International, vol.8, issue.4, 2013. ,
DOI : 10.1586/epr.11.20
URL : http://doi.org/10.1155/2013/485034
Multi-population genomic prediction using a multi-task Bayesian learning model, BMC Genetics, vol.15, issue.1, p.53, 2014. ,
DOI : 10.1186/1471-2105-11-529
URL : https://bmcgenet.biomedcentral.com/track/pdf/10.1186/1471-2156-15-53?site=bmcgenet.biomedcentral.com
Machine learning-based prediction of drug???drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties, Journal of the American Medical Informatics Association, vol.42, issue.(Suppl 9), pp.278-286, 2014. ,
DOI : 10.1093/nar/gkt1031
The Human Genome Project: lessons from large-scale biology, Science, issue.5617, pp.300286-90, 2003. ,
A unified architecture for natural language processing, Proceedings of the 25th international conference on Machine learning, ICML '08 ,
DOI : 10.1145/1390156.1390177
Support-vector networks, Machine Learning, vol.1, issue.3, pp.273-297, 1995. ,
DOI : 10.1007/BF00994018
Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis, PLoS Genetics, vol.17, issue.3, p.1003394, 2013. ,
DOI : 10.1371/journal.pgen.1003394.s009
Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis, PLoS Genetics, vol.17, issue.3, p.1003394, 2013. ,
DOI : 10.1371/journal.pgen.1003394.s009
Innovation in the pharmaceutical industry: New estimates of R&D costs, Journal of Health Economics, vol.47, pp.20-33, 2016. ,
An introduction to generalized linear models, 2008. ,
Identifying human MHC supertypes using bioinformatic methods, The Journal of Immunology, vol.172, issue.7, pp.4314-4323, 2004. ,
Prediction of human population responses to toxic compounds by a collaborative competition, Nature Biotechnology, vol.123, issue.9, pp.933-973, 2015. ,
DOI : 10.1021/ci100050t
URL : https://hal.archives-ouvertes.fr/hal-01246684
Least Angle Regression. The Annals of Statistics, pp.407-499, 2004. ,
Pharmacogenomics?drug disposition , drug targets, and side effects, The New England journal of medicine, vol.348, issue.6, pp.538-587, 2003. ,
Learning multiple tasks with kernel methods, Journal of Machine Learning Research, pp.615-637, 2005. ,
Regularized multi--task learning, Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '04, pp.109-117, 2004. ,
DOI : 10.1145/1014052.1014067
Sparse High-Dimensional Models in Economics, Annual Review of Economics, vol.3, issue.1, pp.291-317, 2011. ,
DOI : 10.1146/annurev-economics-061109-080451
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3196636
On the Properties of Bit String-Based Measures of Chemical Similarity, Journal of Chemical Information and Computer Sciences, vol.38, issue.3, pp.379-386, 1998. ,
DOI : 10.1021/ci970437z
Genetic polymorphism of CYP2C9 and its effect on warfarin maintenance dose requirement in patients undergoing anticoagulation therapy, Pharmacogenetics, vol.5, issue.6, pp.389-392, 1995. ,
DOI : 10.1097/00008571-199512000-00008
Multi-Task Learning for Stock Selection, Advances in Neural Information Processing Systems 9 ,
INDI: a computational framework for inferring drug interactions and their associated recommendations, Molecular Systems Biology, vol.298, issue.592, p.592, 2012. ,
DOI : 10.1517/17425250902926099
URL : http://msb.embopress.org/content/msb/8/1/592.full.pdf
The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity, Human Mutation, vol.36, issue.5, pp.513-523, 2015. ,
Leveraging Information Across HLA Alleles/Supertypes Improves Epitope Prediction, Journal of Computational Biology, vol.14, issue.6, pp.736-746, 2007. ,
DOI : 10.1089/cmb.2007.R013
URL : http://www.cs.toronto.edu/~jenn/papers/LeveragingInfoEpitopePredictionJCB2007.pdf
Ridge Regression: Biased estimation for nonorthogonal problems, Technometrics, vol.12, issue.1, pp.55-67, 1970. ,
Systematic prediction of pharmacodynamic drug-drug interactions through proteinprotein-interaction network, PLoS Computational Biology, vol.9, issue.3, p.2013 ,
Predicting adverse side effects of drugs, BMC Genomics, vol.12, p.11, 2011. ,
Mining clinical text for signals of adverse drug-drug interactions, Journal of the American Medical Informatics Association, vol.21, issue.2, pp.353-362, 2014. ,
Virtual screening of GPCRs: An in silico chemogenomics approach, BMC Bioinformatics, vol.9, issue.1, p.363, 2008. ,
DOI : 10.1186/1471-2105-9-363
URL : https://hal.archives-ouvertes.fr/hal-00220396
Efficient peptide???MHC-I binding prediction for alleles with few known binders, Bioinformatics, vol.22, issue.Web Server issue, pp.358-366, 2008. ,
DOI : 10.1093/bioinformatics/btl141
URL : https://hal.archives-ouvertes.fr/hal-00433574
Protein-ligand interaction prediction: an improved chemogenomics approach, Bioinformatics, vol.18, issue.Database issue, pp.2149-56, 2008. ,
DOI : 10.1093/bioinformatics/18.suppl_1.S276
URL : https://hal.archives-ouvertes.fr/hal-00433572
A dirty model for multi-task learning, Advances in Neural Information Processing Systems, pp.964-972, 2010. ,
Adjusting batch effects in microarray expression data using empirical Bayes methods, Biostatistics, vol.30, issue.4, pp.118-145, 2007. ,
DOI : 10.1093/nar/30.4.e15
Statistical challenges of high-dimensional data, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.367, pp.4237-4253, 1906. ,
Towards a mechanism-based analysis of pharmacodynamic drug?drug interactions in vivo, Pharmacology & therapeutics, vol.106, issue.1, pp.1-18, 2005. ,
The Toxicity Data Landscape for Environmental Chemicals, Environmental Health Perspectives, vol.117, issue.5, pp.685-695, 2009. ,
DOI : 10.1289/ehp.0800168
KEGG as a reference resource for gene and protein annotation, Nucleic Acids Research, vol.44, issue.D1, pp.457-462, 2016. ,
DOI : 10.1021/ci200367w
Momentum grows to make 'personalized' medicine more 'precise', Nature Medicine, vol.1, issue.3, pp.249-249, 2013. ,
DOI : 10.1186/2001-1326-1-7
Systematic identification of proteins that elicit drug side effects, Molecular Systems Biology, vol.6, issue.1, p.663, 2013. ,
DOI : 10.1016/j.jbi.2010.04.006
Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm, Nature Protocols, vol.4, issue.7, pp.1073-81, 2009. ,
DOI : 10.1101/gr.772403
DrugBank 4.0: shedding new light on drug metabolism, Nucleic Acids Research, vol.40, issue.D1, pp.1091-1097, 2014. ,
DOI : 10.1177/0091270003043005001
Incidence of Adverse Drug Reactions in Hospitalized Patients, JAMA, vol.279, issue.15, pp.2791200-1205, 1998. ,
DOI : 10.1001/jama.279.15.1200
Deep learning, Nature, vol.9, issue.7553, pp.436-444, 2015. ,
DOI : 10.1007/s10994-013-5335-x
Multi-level lasso for sparse multi-task regression, Proceedings of the 29th International Conference on Machine Learning, pp.361-368, 2012. ,
Information theory, inference and learning algorithms, 2003. ,
The Pharmacophore Kernel for Virtual Screening with Support Vector Machines, Journal of Chemical Information and Modeling, vol.46, issue.5, pp.2003-2017, 2014. ,
DOI : 10.1021/ci060138m
An integrated map of genetic variation from 1,092 human genomes, Nature, issue.7422, pp.49156-65, 2012. ,
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
Stability selection, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.7, issue.4, pp.417-473, 2010. ,
DOI : 10.1186/1471-2105-9-307
URL : http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2010.00740.x/pdf
Frequency of adverse drug reactions in hospitalized patients: a systematic review and meta-analysis, Pharmacoepidemiology and Drug Safety, vol.24, issue.5, pp.1139-1154, 2012. ,
DOI : 10.7705/biomedica.v26i1.1392
Deep learning in bioinformatics, Briefings in Bioinformatics, vol.13, issue.3, 2016. ,
DOI : 10.1109/ICRA.2015.7139550
URL : http://arxiv.org/pdf/1603.06430
Relating drug-protein interaction network with drug side effects, Bioinformatics, vol.26, issue.12, pp.522-528, 2012. ,
DOI : 10.1093/bioinformatics/btq176
URL : https://academic.oup.com/bioinformatics/article-pdf/28/18/i522/679865/bts383.pdf
Multi-task multiple kernel relationship learning. arXiv preprint, 2016. ,
DOI : 10.1137/1.9781611974973.77
URL : http://epubs.siam.org/doi/pdf/10.1137/1.9781611974973.77
Genome-wide approaches to identify pharmacogenetic contributions to adverse drug reactions. The pharmacogenomics journal, pp.23-33, 2009. ,
DOI : 10.1038/tpj.2008.4
URL : http://www.nature.com/tpj/journal/v9/n1/pdf/tpj20084a.pdf
Introductory Lectures on Convex Optimization, 2004. ,
DOI : 10.1007/978-1-4419-8853-9
Multi-task feature selection, Statistics Department, 2006. ,
KEGG: Kyoto Encyclopedia of Genes and Genomes, Nucleic Acids Research, vol.26, issue.1, pp.29-34, 1999. ,
DOI : 10.1093/nar/26.1.38
Postmarketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature, BMC Medicine, pp.1-11, 2016. ,
A survey on transfer learning, IEEE Transactions on Knowledge and Data Engineering, vol.22, issue.10, pp.1345-1359, 2010. ,
Design characteristics of the CORRONA CERTAIN study: a comparative effectiveness study of biologic agents for rheumatoid arthritis patients, BMC Musculoskeletal Disorders, vol.11, issue.1, p.113, 2014. ,
DOI : 10.1056/NEJMp0901355
Predicting drug side-effect profiles: a chemical fragment-based approach, BMC Bioinformatics, vol.12, issue.1, p.169, 2011. ,
DOI : 10.1093/biostatistics/kxp008
URL : https://hal.archives-ouvertes.fr/inserm-00663945
Active task selection for multi-task learning. arXiv preprint, 2016. ,
Clustering of individuals given SNPs similarity based on normalized mutual information: F7 SNPs in the GAIT sample, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.123-126, 2007. ,
DOI : 10.1109/IEMBS.2007.4352238
Supervised classification in continuous domains with Bayesian networks, 2010. ,
Sune Frankild, et al. A community resource benchmarking predictions of peptide binding to MHC-I molecules ,
Modified disease activity scores that include twenty-eight-joint counts development and validation in a prospective longitudinal study of patients with rheumatoid arthritis, Arthritis & Rheumatism, vol.20, issue.1, pp.44-48, 1995. ,
DOI : 10.1002/art.1780281203
Multi-population GWA mapping via multi-task regularized regression, Bioinformatics, vol.23, issue.2, pp.208-216, 2010. ,
DOI : 10.1002/gepi.210
A Unified Multitask Architecture for Predicting Local Protein Properties, PLoS ONE, vol.35, issue.3, p.2012 ,
DOI : 10.1371/journal.pone.0032235.s001
URL : http://doi.org/10.1371/journal.pone.0032235
Graph kernels for chemical informatics, Neural networks : the official journal of the International Neural Network Society, pp.1093-110, 2005. ,
DOI : 10.1016/j.neunet.2005.07.009
Gaussian processes for machine learning, 2006. ,
Deep Learning for Health Informatics, IEEE Journal of Biomedical and Health Informatics, vol.21, issue.1, 2016. ,
DOI : 10.1109/JBHI.2016.2636665
Pharmacogenomics in the clinic, Nature, vol.526, issue.7573, pp.343-50, 2015. ,
Asymptotic distribution and sparsistency for l1-penalized parametric m-estimators with applications to linear SVM and logistic regression. arXiv preprint arXiv:0908, 1940. ,
Using Extended-Connectivity Fingerprints with Laplacian-Modified Bayesian Analysis in High-Throughput Screening Follow-Up, Journal of Biomolecular Screening, vol.48, issue.7, pp.682-688, 2005. ,
DOI : 10.1021/jm049254b
Extended-Connectivity Fingerprints, Journal of Chemical Information and Modeling, vol.50, issue.5, pp.742-54, 2010. ,
DOI : 10.1021/ci100050t
Mapping Adverse Drug Reactions in Chemical Space, Journal of Medicinal Chemistry, vol.52, issue.9, pp.3103-3107, 2009. ,
DOI : 10.1021/jm801546k
Admissions caused by adverse drug events to internal medicine and emergency departments in hospitals: a longitudinal population-based study, European Journal of Clinical Pharmacology, vol.58, issue.4, pp.285-291, 2002. ,
DOI : 10.1007/s00228-002-0467-0
Kernel methods in computational biology, 2004. ,
MutationTaster evaluates disease-causing potential of sequence alterations, Nature Methods, vol.35, issue.8, pp.575-581, 2010. ,
DOI : 10.1038/nmeth0810-575
An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations, Nature Genetics, vol.90, issue.7, pp.825-830, 2012. ,
DOI : 10.1080/01621459.1995.10476572
URL : https://hal.archives-ouvertes.fr/hal-01267792
Adverse drug reactions: role of pharmacogenomics, Pharmacological Research, vol.49, issue.4, pp.363-373, 2004. ,
DOI : 10.1016/j.phrs.2003.05.003
Metabolic Network Prediction of Drug Side Effects, Cell Systems, vol.2, issue.3, pp.209-213, 2016. ,
DOI : 10.1016/j.cels.2016.03.001
Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis, Nature communications, vol.7, p.12460, 2016. ,
A Sparse-Group Lasso, Journal of Computational and Graphical Statistics, vol.67, issue.2, pp.231-245, 2013. ,
DOI : 10.1111/j.1467-9868.2005.00503.x
A tutorial on support vector regression, Statistics and Computing, vol.14, issue.3, pp.199-222, 2004. ,
DOI : 10.1023/B:STCO.0000035301.49549.88
Clinical application of pharmacogenetics, Trends in Molecular Medicine, vol.7, issue.5, pp.201-204, 2001. ,
DOI : 10.1016/S1471-4914(01)01986-4
A personalized medicine approach to biologic treatment of rheumatoid arthritis: A preliminary treatment algorithm, Rheumatology, vol.51, issue.4, pp.600-609, 2012. ,
A Genome-Wide Association Study Confirms VKORC1, CYP2C9, and CYP4F2 as Principal Genetic Determinants of Warfarin Dose, PLoS Genetics, vol.271, issue.3, p.1000433, 2009. ,
DOI : 10.1371/journal.pgen.1000433.s007
Pharmgkb: the pharmacogenomics knowledge base, Pharmacogenomics: Methods and Protocols, pp.311-320, 2013. ,
Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B (Methodological), pp.267-288, 1996. ,
DOI : 10.1111/j.1467-9868.2011.00771.x
Improving the Human Hazard Characterization of Chemicals: A Tox21 Update, Environmental Health Perspectives, vol.121, issue.7, pp.756-765, 2013. ,
DOI : 10.1289/ehp.1205784
Development and validation of the european league against rheumatism response criteria for rheumatoid arthritis: Comparison with the preliminary american college of rheumatology and the world health organization/international league against rheumatism criteria, Arthritis & Rheumatism, vol.38, issue.1, pp.34-40, 1996. ,
DOI : 10.1002/art.1780390105
Single Nucleotide Polymorphism in Cytogenetically Normal Acute Myeloid Leukemia: SNP rs11554137 Is an Adverse Prognostic Factor, Journal of Clinical Oncology, vol.28, issue.14, pp.2356-2364, 2010. ,
DOI : 10.1200/JCO.2009.27.6899
Random lasso, The Annals of Applied Statistics, vol.5, issue.1, pp.468-485, 2011. ,
DOI : 10.1214/10-AOAS377
URL : http://doi.org/10.1214/10-aoas377
On multiplicative multitask feature learning, Advances in Neural Information Processing Systems, pp.2411-2419, 2014. ,
Inheritance and Drug Response, New England Journal of Medicine, vol.348, issue.6, pp.529-537, 2003. ,
DOI : 10.1056/NEJMra020021
Inferring latent task structure for Multitask Learning by Multiple Kernel Learning, BMC Bioinformatics, vol.11, issue.Suppl 8, p.5, 2010. ,
DOI : 10.1186/1471-2105-11-S8-S5
URL : https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/1471-2105-11-S8-S5?site=bmcbioinformatics.biomedcentral.com
Predicting in vivo drug interactions from in vitro drug discovery data, Nature reviews. Drug discovery, vol.4, issue.10, pp.825-833, 2005. ,
Identifying genetic risk factors for serious adverse drug reactions : current progress and challenges, Nature reviews. Drug discovery, vol.6, issue.november, pp.904-916, 2007. ,
Prediction with Gaussian processes: From linear regression to linear prediction and beyond. Learning in graphical models, 1998. ,
DOI : 10.1007/978-94-011-5014-9_23
URL : http://www.ncrg.aston.ac.uk/Papers/postscript/NCRG_97_012.ps.Z
Compound Cytotoxicity Profiling Using Quantitative High-Throughput Screening, Environmental Health Perspectives, vol.116, issue.3, p.284, 2008. ,
DOI : 10.1289/ehp.10727
URL : http://europepmc.org/articles/pmc2265061?pdf=render
Improving prediction accuracy of tumor classification by reusing genes discarded during gene selection, BMC genomics, vol.9, issue.1, p.1, 2008. ,
Model selection and estimation in regression with grouped variables, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.58, issue.1, pp.49-67, 2006. ,
DOI : 10.1198/016214502753479356
URL : http://www2.isye.gatech.edu/~myuan/papers/glasso.final.pdf
Non-coding genetic variants in human disease: Figure 1., Human Molecular Genetics, vol.97, issue.R1, pp.102-110, 2015. ,
DOI : 10.1038/ng.3304
Predicting Drug???Drug Interactions: An FDA Perspective, The AAPS Journal, vol.11, issue.2, pp.300-306, 2009. ,
DOI : 10.1208/s12248-009-9106-3
URL : http://europepmc.org/articles/pmc2691466?pdf=render
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
The Adaptive Lasso and Its Oracle Properties, Journal of the American Statistical Association, vol.101, issue.476, pp.1418-1429, 2006. ,
DOI : 10.1198/016214506000000735
URL : http://cbio.ensmp.fr/~jvert/svn/bibli/local/Zou2006adaptive.pdf