H. Xie and F. Frueh, Pharmacogenomics steps toward personalized medicine, Personalized Medicine, vol.2, issue.4, pp.325-332, 2005.
DOI : 10.2217/17410541.2.4.325

Y. Garten, A. Coulet, and R. Altman, Recent progress in automatically extracting information from the pharmacogenomic literature, Pharmacogenomics, vol.11, issue.10, pp.1467-89, 2010.
DOI : 10.2217/pgs.10.136

URL : https://hal.archives-ouvertes.fr/inria-00549699

M. Whirl-carrillo, Pharmacogenomics Knowledge for Personalized Medicine, Clinical Pharmacology & Therapeutics, vol.92, issue.4, pp.414-431, 2012.
DOI : 10.1038/clpt.2010.279

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3660037

J. Ioannidis, To Replicate or Not to Replicate: The Case of Pharmacogenetic Studies: Have Pharmacogenomics Failed, or Do They Just Need Larger-Scale Evidence and More Replication?, Circulation: Cardiovascular Genetics, vol.6, issue.4, pp.413-421, 2013.
DOI : 10.1161/CIRCGENETICS.113.000106

I. Zineh, M. Pacanowski, and J. Woodcock, Pharmacogenetics and Coumarin Dosing ??? Recalibrating Expectations, New England Journal of Medicine, vol.369, issue.24, pp.2273-2278, 2013.
DOI : 10.1056/NEJMp1314529

C. Bizer, T. Heath, and T. Berners-lee, Linked Data - The Story So Far, International Journal on Semantic Web and Information Systems, vol.5, issue.3, pp.1-22, 2009.
DOI : 10.4018/jswis.2009081901

E. Antezana, M. Kuiper, and V. Mironov, Biological knowledge management: the emerging role of the Semantic Web technologies, Briefings in Bioinformatics, vol.10, issue.4, pp.392-407, 2009.
DOI : 10.1093/bib/bbp024

A. Callahan, J. Cruz-toledo, P. Ansell, and M. Dumontier, Bio2RDF Release 2: Improved Coverage, Interoperability and Provenance of Life Science Linked Data, Proceedings of the 10th European Semantic Web Conference, ESWC 2013, pp.200-212, 2013.
DOI : 10.1007/978-3-642-38288-8_14

S. Jupp, J. Malone, J. Bolleman, M. Brandizi, M. Davies et al., The EBI RDF platform: linked open data for the life sciences, Bioinformatics, vol.30, issue.9, pp.1338-1347, 2014.
DOI : 10.1093/bioinformatics/btt765

A. Kinjo, Protein Data Bank Japan (PDBj): maintaining a structural data archive and resource description framework format, Nucleic Acids Research, vol.40, issue.D1, pp.453-60, 2012.
DOI : 10.1093/nar/gkr811

URL : http://doi.org/10.1093/nar/gkr811

B. Good and M. Wilkinson, The life sciences semantic web is full of creeps! Brief Bioinform, pp.275-86, 2006.

M. Marshall, R. Boyce, H. Deus, J. Zhao, E. Willighagen et al., Emerging practices for mapping and linking life sciences data using RDF ??? A case series, Web Semantics: Science, Services and Agents on the World Wide Web, vol.14, pp.2-13, 2012.
DOI : 10.1016/j.websem.2012.02.003

. Pharmgkb, Levels of evidence of annotations, 2016.

D. Wishart, C. Knox, A. Guo, D. Cheng, S. Shrivastava et al., DrugBank: a knowledgebase for drugs, drug actions and drug targets, Nucleic Acids Research, vol.36, issue.Database, pp.901-907, 2008.
DOI : 10.1093/nar/gkm958

URL : http://doi.org/10.1093/nar/gkm958

M. Landrum, J. Lee, G. Riley, W. Jang, W. Rubinstein et al., ClinVar: public archive of relationships among sequence variation and human phenotype, Nucleic Acids Research, vol.42, issue.D1, pp.980-985, 2014.
DOI : 10.1093/nar/gkt1113

URL : http://doi.org/10.1093/nar/gkt1113

M. Kuhn, M. Campillos, I. Letunic, L. Jensen, and P. Bork, A side effect resource to capture phenotypic effects of drugs, Molecular Systems Biology, vol.6, issue.1, p.343, 2010.
DOI : 10.1093/nar/gkm958

M. Kuhn, I. Letunic, L. Jensen, and P. Bork, The SIDER database of drugs and side effects, Nucleic Acids Research, vol.44, issue.D1, pp.1075-1084, 2016.
DOI : 10.1093/nar/gkv1075

M. Kuhn, I. Letunic, L. Jensen, and P. Bork, The SIDER database of drugs and side effects, Nucleic Acids Research, vol.44, issue.D1, pp.1075-1084, 1075.
DOI : 10.1093/nar/gkv1075

A. Wagner, A. Coffman, B. Ainscough, N. Spies, Z. Skidmore et al., DGIdb 2.0: mining clinically relevant drug???gene interactions, Nucleic Acids Research, vol.44, issue.D1, pp.1036-1080, 2016.
DOI : 10.1093/nar/gkv1165

J. Piñero, N. Queralt-rosinach, À. Bravo, J. Deu-pons, A. Bauer-mehren et al., DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes, Database, vol.2015, issue.0, p.28, 2015.
DOI : 10.1093/database/bav028

M. Samwald, A. Coulet, I. Huerga, R. Powers, J. Luciano et al., Semantically enabling pharmacogenomic data for the realization of personalized medicine, Pharmacogenomics, vol.13, issue.2, pp.201-213, 2012.
DOI : 10.2217/pgs.11.179

URL : https://hal.archives-ouvertes.fr/hal-00752095

R. Hoehndorf, M. Dumontier, and G. Gkoutos, Identifying aberrant pathways through integrated analysis of knowledge in pharmacogenomics, Bioinformatics, vol.28, issue.16, pp.2169-75, 2012.
DOI : 10.1093/bioinformatics/bts350

A. Coulet, Y. Garten, M. Dumontier, R. Altman, M. Musen et al., Integration and publication of heterogeneous text-mined relationships on the Semantic Web, Journal of Biomedical Semantics, vol.2, issue.Suppl 2, p.10, 2011.
DOI : 10.1186/gb-2005-6-5-r46

URL : https://hal.archives-ouvertes.fr/hal-00585215

V. Bicer, T. Tran, and A. Gossen, Relational Kernel Machines for Learning from Graph-Structured RDF Data, Proceedings of the 8th Extended Semantic Web Conference, pp.47-62, 2011.
DOI : 10.1007/978-3-642-04174-7_19

Y. Huang, V. Tresp, M. Bundschus, A. Rettinger, and H. Kriegel, Multivariate Prediction for Learning on the Semantic Web, Proceedings of the 20th International Conference on Inductive Logic Programming, pp.92-104, 2010.
DOI : 10.1007/978-3-642-21295-6_13

A. Thor, P. Anderson, L. Raschid, S. Navlakha, B. Saha et al., Link Prediction for Annotation Graphs Using Graph Summarization, Proceedings of the 10th International Conference on The Semantic Web -Volume Part I ISWC'11, pp.714-743, 2011.
DOI : 10.1007/978-3-642-12683-3_30

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

U. Lösch, S. Bloehdorn, and A. Rettinger, Graph Kernels for RDF Data, Proceedings of the 9th Extended Semantic Web Conference, ESWC 2012, pp.134-182, 2012.
DOI : 10.1007/978-3-642-30284-8_16

G. De-vries, A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF Data, Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, Part I, ECML PKDD 2013, pp.606-627, 2013.
DOI : 10.1007/978-3-642-40988-2_39

C. Brenninkmeijer, I. Dunlop, C. Goble, A. Gray, S. Pettifer et al., Computing identity co-reference across drug discovery datasets, Proceedings of the 6th International Workshop on Semantic Web Applications and Tools for Life Sciences, SWAT4LS 2013. CEUR Workshop Proceedings

J. Volz, C. Bizer, M. Gaedke, and G. Kobilarov, Discovering and Maintaining Links on the Web of Data, Proceedings of the 8th International Semantic Web Conference, pp.650-65, 2009.
DOI : 10.1007/978-3-642-04930-9_41

P. Heim, S. Lohmann, and T. Stegemann, Interactive Relationship Discovery via the Semantic Web, Proceedings of the 7th Extended Semantic Web Conference, pp.303-320, 2011.
DOI : 10.1007/978-3-642-13486-9_21

G. De-vries and S. De-rooij, Substructure counting graph kernels for machine learning from RDF data, Web Semantics: Science, Services and Agents on the World Wide Web, vol.35, pp.71-84, 2015.
DOI : 10.1016/j.websem.2015.08.002

R. Kondor and J. Lafferty, Diffusion kernels on graphs and other discrete input spaces, Proceedings of the 19th International Conference on Machine Learning, pp.315-337, 2002.

DOI : 10.1142/9789814366496_0040

K. Dalleau, N. Ndiaye, and A. Coulet, Suggesting valid pharmacogenes by mining linked data, Proceedings of the 8th Semantic Web Applications and Tools for Life Sciences International Conference, SWAT4LS 2015. CEUR Workshop Proceedings 1546, pp.49-58, 2015.
DOI : 10.1186/s13326-017-0125-1

URL : https://hal.archives-ouvertes.fr/hal-01239568

N. Hansen, S. Brunak, and R. Altman, Generating Genome-Scale Candidate Gene Lists for Pharmacogenomics, Clinical Pharmacology & Therapeutics, vol.36, issue.2, pp.183-192, 2009.
DOI : 10.1093/nar/gki022

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2729176

DOI : 10.1142/9789814295291_0033

DOI : 10.1142/9789814583220_0032

M. Dumontier and N. Villanueva-rosales, Towards pharmacogenomics knowledge discovery with the semantic web, Briefings in Bioinformatics, vol.10, issue.2, pp.153-63, 2009.
DOI : 10.1093/bib/bbn056

A. Coulet, M. Smail-tabbone, A. Napoli, and M. Devignes, Ontology-Based Knowledge Discovery in Pharmacogenomics, Adv Exp Med Biol, vol.696, pp.357-66, 2011.
DOI : 10.1007/978-1-4419-7046-6_36

URL : https://hal.archives-ouvertes.fr/inria-00585072

T. Imanishi and H. Nakaoka, Hyperlink Management System and ID Converter System: enabling maintenance-free hyperlinks among major biological databases, Nucleic Acids Research, vol.37, issue.Web Server, pp.17-22, 2009.
DOI : 10.1093/nar/gkp355

URL : http://doi.org/10.1093/nar/gkp355

K. Dalleau, biojp2rdf ? a tool to rdfize biodb.jp data, under mit licence. https://github, 2016.

K. Zeng, O. Bodenreider, J. Kilbourne, and S. Nelson, Rxnav: Towards an integrated view on drug information, Proceedings of the 12th World Congress on Health (Medical) Informatics, p.386, 2007.

L. Breiman, Random Forests, Machine Learning, vol.45, issue.1, pp.5-32, 2001.
DOI : 10.1023/A:1010933404324

C. Leistner, A. Saffari, and H. Bischof, MIForests: Multiple-Instance Learning with Randomized Trees, Proceedings of the 11th European Conference on Computer Vision, Part IV, ECCV 2010, pp.29-42, 2010.
DOI : 10.1007/978-3-642-15567-3_3

J. Amores, Multiple instance classification: Review, taxonomy and comparative study, Artificial Intelligence, vol.201, pp.81-105, 2013.
DOI : 10.1016/j.artint.2013.06.003

G. Cawley and N. Talbot, On over-fitting in model selection and subsequent selection bias in performance evaluation, J Mach Learn Res, vol.11, pp.2079-107, 2010.

C. Mayo, J. Bertran-alamillo, M. Molina-vila, A. Giménez-capitán, C. Costa et al., in lung cancer: perspectives and clinical applications, Pharmacogenomics, vol.13, issue.7, pp.789-802, 2012.
DOI : 10.2217/pgs.12.54

R. De-mello, P. Madureira, L. Carvalho, A. Araújo, M. O-'brien et al., fusions: current developments and personalized therapies for patients with advanced non-small-cell lung cancer, Pharmacogenomics, vol.14, issue.14, pp.1765-77, 2013.
DOI : 10.2217/pgs.13.177

T. Okabe, I. Okamoto, S. Tsukioka, J. Uchida, T. Iwasa et al., Synergistic antitumor effect of S-1 and the epidermal growth factor receptor inhibitor gefitinib in non-small cell lung cancer cell lines: role of gefitinib-induced down-regulation of thymidylate synthase, Molecular Cancer Therapeutics, vol.7, issue.3, pp.599-606, 2008.
DOI : 10.1158/1535-7163.MCT-07-0567

H. Kim, I. Choi, C. Kim, H. Kim, A. Oshima et al., Three-gene predictor of clinical outcome for gastric cancer patients treated with chemotherapy, The Pharmacogenomics Journal, vol.6, issue.2, pp.119-146, 2012.
DOI : 10.1038/tpj.2010.87

Y. Sato, N. Yamamoto, H. Kunitoh, Y. Ohe, H. Minami et al., Genome-wide association study on overall survival of advanced nonsmall cell lung cancer patients treated with carboplatin and paclitaxel, J Thorac Oncol Off Publ Int Assoc Study Lung Cancer, vol.6, issue.1, pp.132-140, 2011.

H. Saigo, S. Nowozin, T. Kadowaki, T. Kudo, and K. Tsuda, gBoost: a mathematical programming approach to graph classification and regression, Machine Learning, vol.67, issue.2, pp.69-89, 2009.
DOI : 10.1007/s10994-008-5089-z

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

X. Yan and J. Han, gspan: Graph-based substructure pattern mining, Proceedings of the 2002 IEEE International Conference on Data Mining, ICDM 2002 IEEE Computer Society, pp.721-725, 2002.

Y. Marzougui, pgx-lod-mining ? adapting mustard to pgx linked data. https://github.com/yassmarzou/pgx-lod-mining, 2016.