S. Morgan, P. Grootendorst, J. Lexchin, C. Cunningham, D. Et et al., The Cost of Drug Development: A Systematic Review, vol.100, pp.4-17, 2011.


L. Weng, L. Zhang, Y. Peng, and E. Huang, « Pharmacogenetics and pharmacogenomics: a bridge to individualized cancer therapy, Pharmacogenomics, vol.14, issue.3, pp.315-339, 2013.

Y. Cha, T. Erez, I. J. Reynolds, D. Kumar, J. Ross et al., Drug Repurposing from the Perspective of Pharmaceutical Companies, British Journal of Pharmacology, vol.175, pp.168-80, 2018.

V. Prasad, S. Et, and . Mailankody, Research and Development Spending to Bring a Single Cancer Drug to Market and Revenues After Approval, JAMA Internal Medicine, vol.177, issue.11, pp.1569-75, 2017.

S. Pushpakom, F. Iorio, P. A. Eyers, K. J. Escott, and S. Hopper,

A. Doig, Drug Repurposing: Progress, Challenges and Recommendations, vol.12

A. Talevi, « Drug repositioning: current approaches and their implications in the precision medicine era, Expert Review of Precision Medicine and Drug Development, vol.3, issue.1, pp.49-61

E. Ozdemir, F. Sila, R. Halakou, A. Nussinov, and . Gursoy, et Ozlem Keskin. « Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application

. Repurposing, Computational Methods for Drug Repurposing, édité par Quentin Vanhaelen, pp.1-21, 1903.

T. Chou and . Basis, Experimental Design, and Computerized Simulation of Synergism and Antagonism in Drug Combination Studies, Pharmacological Reviews, vol.58, issue.3, pp.621-81, 2006.

S. Li, Y. Cao, L. Li, H. Zhang, X. Lu et al., Building the Drug-GO Function Network to Screen Significant Candidate Drugs for Myasthenia Gravis, PloS One, vol.14, 2019.

J. Foucquier and . Guedj, Analysis of drug combinations: current methodological landscape, Pharmacology Research & Perspectives, vol.3, issue.3, 2015.


H. Huang, P. Zhang, X. A. Qu, P. Sanseau, and Y. Et-lun, « Systematic prediction of drug combinations based on clinical side-effects


. Health-quality-ontario, Pharmacogenomic Testing for Psychotropic Medication Selection: A Systematic Review of the Assurex GeneSight Psychotropic Test, Ontario Health Technology Assessment Series, vol.17, issue.4, pp.1-39, 2017.

X. Liu, J. Petit, P. Ezan, J. Gyger, P. Magistretti et al.,

, The Psychostimulant Modafinil Enhances Gap Junctional Communication in Cortical Astrocytes, Neuropharmacology, vol.75, pp.533-571, 2013.


B. Brookshire, Scientists Say: Glia, Science News for Students

S. Jäkel and L. Dimou, Glial Cells and Their Function in the Adult Brain: A Journey through the History of Their Ablation, vol.11, 2017.


J. Zuchero, B. A. Bradley, and . Barres, Glia in Mammalian Development and Disease

, Development, vol.142, pp.3805-3814


A. Duchêne, M. Perier, Y. Zhao, and X. Liu,

C. Piérard, Impact of Astroglial Connexins on Modafinil Pharmacological Properties ». Sleep, vol.39, issue.6, pp.1283-92, 2016.

D. C. Faye, O. Curé, and G. Blin, A survey of RDF storage approaches, Revue Africainede la Recherche en Informatique et Mathématiques Appliquées, vol.15, pp.11-35, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01299496

C. Boettiger, rdflib: A high level wrapper around the redland package for common rdf applications (Version 0.1.0). Zenodo, 2018.

C. Bettembourg, O. Dameron, A. Bretaudeau, and F. Legeai, AskOmics : Intégration et interrogation de réseaux de régulation génomique et post-génomique, OVIVE (INtégration de sources/masses de données hétérogènes et Ontologies, dans le domaine des sciences du VIVant et de l'Environnement), pp.7-01184903, 2015.

, UniProt: a worldwide hub of protein knowledge, Pages D506-D515, vol.47, 2019.

E. Demir, P. Michael, S. Cary, K. Paley, C. Fukuda et al.,

G. Wu, « The BioPAX community standard for pathway data sharing », Nature Biotechnology, vol.28, p.935, 2010.

D. S. Wishart, Y. D. Feunang, A. C. Guo, E. J. Lo, A. Marcu et al.,

N. Assempour, I. Iynkkaran, Y. Liu, A. Maciejewski, N. Gale et al., DrugBank 5.0: a major update to the DrugBank database for 2018, Nucleic Acids Res, 2017.

S. Kim, J. Chen, T. Cheng, A. Gindulyte, J. He et al., PubChem 2019 update: improved access to chemical data, Nucleic Acids Res, vol.47, issue.D1, pp.1102-1109, 2019.

A. D. Rouillard, G. W. Gundersen, N. F. Fernandez, Z. Wang, C. D. Monteiro et al., The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins. Database (Oxford), p.100, 2016.

M. Whirl-carrillo, E. M. Mcdonagh, J. M. Hebert, L. Gong, K. Sangkuhl et al., Pharmacogenomics Knowledge for Personalized Medicine, Clinical Pharmacology & Therapeutics, vol.92, issue.4, pp.414-417, 2012.

M. Kanehisa, Y. Sato, M. Furumichi, K. Morishima, and M. Tanabe, New approach for understanding genome variations in KEGG, Nucleic Acids Res, vol.47, pp.590-595, 2019.

A. Gaulton, L. J. Bellis, and A. P. Bento, ChEMBL: a large-scale bioactivity database for drug discovery, Nucleic Acids Res, vol.40, pp.1100-1107, 2012.

C. Kelsy, A. H. Cotto, Y. Wagner, S. Feng, . Kiwala et al., DGIdb 3.0: a redesign and expansion of the drug-gene interaction database, Pages D1068-D1073, vol.46, 2018.

P. J. Kersey, J. E. Allen, A. Allot, M. Barba, S. Boddu et al.,

C. Davis, N. Grabmueller, Z. Kumar, T. Liu, B. Maurel et al.,

V. Naamati, C. K. Newman, D. M. Ong, N. Bolser, K. L. Silva et al.,

A. Staines and . Yates, Ensembl Genomes 2018: an integrated omics infrastructure for non-vertebrate species, Nucleic Acids Research, vol.46, issue.D1, pp.802-808, 2018.

D. N. Slenter, M. Kutmon, K. Hanspers, A. Riutta, J. Windsor et al., WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research, Nucleic Acids Research, 2017.