G. J. Morgan, B. A. Walker, and F. Davies, The genetic architecture of multiple myeloma, Nature Reviews Cancer, vol.214, issue.5, pp.335-383, 2012.
DOI : 10.1002/path.2279

F. Zhan, The molecular classification of multiple myeloma, Blood, vol.108, issue.6, pp.2020-2028, 2006.
DOI : 10.1182/blood-2005-11-013458

O. Decaux, Prediction of Survival in Multiple Myeloma Based on Gene Expression Profiles Reveals Cell Cycle and Chromosomal Instability Signatures in High-Risk Patients and Hyperdiploid Signatures in Low-Risk Patients: A Study of the Intergroupe Francophone du My??lome, Journal of Clinical Oncology, vol.26, issue.29, pp.4798-4805, 2008.
DOI : 10.1200/JCO.2007.13.8545

J. D. Shaughnessy, A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1, Blood, vol.109, issue.6, pp.2276-84, 2007.
DOI : 10.1182/blood-2006-07-038430

H. Avet-loiseau, Prognostic Significance of Copy-Number Alterations in Multiple Myeloma, Journal of Clinical Oncology, vol.27, issue.27, pp.4585-90, 2009.
DOI : 10.1200/JCO.2008.20.6136

A. Broyl, Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients, Blood, vol.116, issue.14, pp.2543-53, 2010.
DOI : 10.1182/blood-2009-12-261032

B. A. Walker, Mutational Spectrum, Copy Number Changes, and Outcome: Results of a Sequencing Study of Patients With Newly Diagnosed Myeloma, Journal of Clinical Oncology, vol.33, issue.33, pp.3911-3931, 2015.
DOI : 10.1200/JCO.2014.59.1503

N. U. Rashid, Differential and limited expression of mutant alleles in multiple myeloma, Blood, vol.124, issue.20, pp.3110-3117, 2014.
DOI : 10.1182/blood-2014-04-569327

M. R. Mansour, An oncogenic super-enhancer formed through somatic mutation of a noncoding intergenic element, Science, vol.1, issue.3, pp.1373-1380, 2014.
DOI : 10.1002/gcc.2870010303

M. Kanehisa and S. Goto, KEGG: Kyoto Encyclopedia of Genes and Genomes, Nucleic Acids Research, vol.28, issue.1, pp.27-30, 2000.
DOI : 10.1093/nar/28.1.27

C. F. Schaefer, PID: the Pathway Interaction Database, Nucleic Acids Research, vol.37, issue.suppl_1, pp.674-683, 2009.
DOI : 10.1093/nar/gkn653

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2686461

T. Kelder, WikiPathways: building research communities on biological pathways, Nucleic Acids Research, vol.40, issue.D1, pp.1301-1308, 2012.
DOI : 10.1093/nar/gkr1074

URL : https://academic.oup.com/nar/article-pdf/40/D1/D1301/9478063/gkr1074.pdf

E. Wingender, The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation, Briefings in Bioinformatics, vol.9, issue.4, pp.326-332, 2008.
DOI : 10.1093/bib/bbn016

S. Boué, Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems, Database, vol.2015, issue.0, p.30, 2015.
DOI : 10.1093/database/bav030

P. Khatri, M. Sirota, and A. J. Butte, Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges, PLoS Computational Biology, vol.23, issue.2, p.1002375, 2012.
DOI : 10.1371/journal.pcbi.1002375.s006

URL : http://doi.org/10.1371/journal.pcbi.1002375

G. Bindea, ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks, Bioinformatics, vol.25, issue.8, pp.1091-1094, 2009.
DOI : 10.1093/bioinformatics/btp101

N. L. Catlett, Reverse causal reasoning: applying qualitative causal knowledge to the interpretation of high-throughput data, BMC Bioinformatics, vol.14, issue.1, p.340, 2013.
DOI : 10.1200/JCO.2009.25.3641

F. Martin, Quantification of biological network perturbations for mechanistic insight and diagnostics using two-layer causal models, BMC Bioinformatics, vol.15, issue.1, p.238, 2014.
DOI : 10.1186/1471-2105-15-238

A. Subramanian, Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles, Proceedings of the National Academy of Sciences, vol.19, issue.18, pp.15545-50, 2005.
DOI : 10.1093/bioinformatics/btg363

URL : http://www.pnas.org/content/102/43/15545.full.pdf

C. Backes, GeneTrail--advanced gene set enrichment analysis, Nucleic Acids Research, vol.35, issue.Web Server, pp.186-92, 2007.
DOI : 10.1093/nar/gkm323

URL : https://academic.oup.com/nar/article-pdf/35/suppl_2/W186/9584774/gkm323.pdf

C. Lefebvre, A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers, Molecular Systems Biology, vol.3909, p.377, 2010.
DOI : 10.1186/gb-2006-7-7-r55

S. W. Kong, W. T. Pu, and P. J. Park, A multivariate approach for integrating genome-wide expression data and biological knowledge, Bioinformatics, vol.22, issue.19, pp.2373-80, 2006.
DOI : 10.1093/bioinformatics/btl401

URL : https://academic.oup.com/bioinformatics/article-pdf/22/19/2373/664010/btl401.pdf

T. Ideker, O. Ozier, B. Schwikowski, and A. Siegel, Discovering regulatory and signalling circuits in molecular interaction networks, Bioinformatics, vol.18, issue.Suppl 1, pp.233-273, 2002.
DOI : 10.1093/bioinformatics/18.suppl_1.S233

URL : https://academic.oup.com/bioinformatics/article-pdf/18/suppl_1/S233/630548/18S233.pdf

K. Komurov, S. Dursun, S. Erdin, and P. Ram, NetWalker: a contextual network analysis tool for functional genomics, BMC Genomics, vol.13, issue.1, p.282, 2012.
DOI : 10.1038/nmeth.1282

URL : http://doi.org/10.1186/1471-2164-13-282

W. Liu, Topologically inferring risk-active pathways toward precise cancer classification by directed random walk, Bioinformatics, vol.29, issue.17, pp.2169-77, 2013.
DOI : 10.1093/bioinformatics/btt373

URL : https://academic.oup.com/bioinformatics/article-pdf/29/17/2169/16919006/btt373.pdf

Ö. N. Yavero?lu, T. Milenkovi?, and N. Pr?ulj, Proper evaluation of alignment-free network comparison methods, Bioinformatics, vol.31, issue.16, pp.2697-2704, 2015.
DOI : 10.1093/bioinformatics/btv170

S. Draghici, A systems biology approach for pathway level analysis, Genome Research, vol.17, issue.10, pp.1537-1582, 2007.
DOI : 10.1101/gr.6202607

URL : http://genome.cshlp.org/content/17/10/1537.full.pdf

H. Avet-loiseau, Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myelome, Blood, vol.109, issue.8, pp.3489-95, 2007.
DOI : 10.1182/blood-2006-08-040410

B. Klein, Positioning NK-??B in multiple myeloma, Blood, vol.115, issue.17, pp.3422-3426, 2010.
DOI : 10.1182/blood-2010-01-264796

URL : http://www.bloodjournal.org/content/bloodjournal/115/17/3422.full.pdf

J. Saez-rodriguez, Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction, Molecular Systems Biology, vol.41, p.331, 2009.
DOI : 10.1038/msb.2008.53

J. Quinlan, Simplifying decision trees, International Journal of Man-Machine Studies, vol.27, issue.3, pp.221-234, 1987.
DOI : 10.1016/S0020-7373(87)80053-6

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

C. Baral, Knowledge Representation, Reasoning and Declarative Problem Solving, 2003.
DOI : 10.1017/CBO9780511543357

A. A. Hagberg, D. A. Schult, and P. J. Swart, Exploring network structure, dynamics, and function using NetworkX, Proceedings of the 7th Python in Science Conference (SciPy2008), pp.11-15, 2008.

R. Team, R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, 2015.

K. Podar, Up-Regulation of c-Jun Inhibits Proliferation and Induces Apoptosis via Caspase-Triggered c-Abl Cleavage in Human Multiple Myeloma, Cancer Research, vol.67, issue.4, pp.1680-1688, 2007.
DOI : 10.1158/0008-5472.CAN-06-1863

F. H. Xu, Interleukin-6-induced inhibition of multiple myeloma cell apoptosis: support for the hypothesis that protection is mediated via inhibition of the JNK/SAPK pathway, Blood, vol.92, pp.241-251, 1998.

M. N. Saha, Targeting p53 via JNK Pathway: A Novel Role of RITA for Apoptotic Signaling in Multiple Myeloma, PLoS ONE, vol.21, issue.1, p.30215, 2012.
DOI : 10.1371/journal.pone.0030215.s005

L. Chen, Identification of early growth response protein 1 (EGR-1) as a novel target for JUN-induced apoptosis in multiple myeloma, Blood, vol.115, issue.1, pp.61-70, 2010.
DOI : 10.1182/blood-2009-03-210526

F. Fan, Targeting Mcl-1 for multiple myeloma (MM) therapy: Drug-induced generation of Mcl-1 fragment Mcl-1128???350 triggers MM cell death via c-Jun upregulation, Cancer Letters, vol.343, issue.2, pp.286-94, 2014.
DOI : 10.1016/j.canlet.2013.09.042

S. Uddin, Overexpression of FoxM1 offers a promising therapeutic target in diffuse large B-cell lymphoma, Haematologica, vol.97, issue.7, pp.1092-100, 2012.
DOI : 10.3324/haematol.2011.053421

C. Gu, FOXM1 is a therapeutic target for high-risk multiple myeloma, Leukemia, vol.30, issue.4, pp.873-882, 2016.
DOI : 10.1182/blood-2014-06-584417

K. Mahtouk, An inhibitor of the EGF receptor family blocks myeloma cell growth factor activity of HB-EGF and potentiates dexamethasone or anti-IL-6 antibody-induced apoptosis, Blood, vol.103, issue.5, pp.1829-1866, 2004.
DOI : 10.1182/blood-2003-05-1510

URL : https://hal.archives-ouvertes.fr/inserm-00130207

K. Mahtouk, Expression of EGF-family receptors and amphiregulin in multiple myeloma. Amphiregulin is a growth factor for myeloma cells, Oncogene, vol.83, issue.21, pp.3512-3524, 2005.
DOI : 10.1093/oxfordjournals.jbchem.a021776

URL : https://hal.archives-ouvertes.fr/inserm-00130206

J. B. Johnston, Targeting the EGFR Pathway for Cancer Therapy, Current Medicinal Chemistry, vol.13, issue.29, pp.3483-3492, 2006.
DOI : 10.2174/092986706779026174

M. Hallek, Signal transduction of interleukin-6 involves tyrosine phosphorylation of multiple cytosolic proteins and activation of Src-family kinases Fyn, Hck, and Lyn in multiple myeloma cell lines, Experimental hematology, vol.25, pp.1367-77, 1997.

A. M. Coluccia, Validation of PDGFR?? and c-Src tyrosine kinases as tumor/vessel targets in patients with multiple myeloma: preclinical efficacy of the novel, orally available inhibitor dasatinib, Blood, vol.112, issue.4, pp.1346-56, 2008.
DOI : 10.1182/blood-2007-10-116590

H. Ishikawa, Requirements of src family kinase activity associated with CD45 for myeloma cell proliferation by interleukin-6, Blood, vol.99, issue.6, pp.2172-2178, 2002.
DOI : 10.1182/blood.V99.6.2172

H. Avet-loiseau, Combining fluorescent in situ hybridization data with ISS staging improves risk assessment in myeloma: an International Myeloma Working Group collaborative project, Leukemia, vol.88, issue.3, pp.711-717, 2013.
DOI : 10.1200/JCO.2011.36.5726

R. Eferl and E. Wagner, AP-1: a double-edged sword in tumorigenesis, Nature Reviews Cancer, vol.3, issue.11, pp.859-68, 2003.
DOI : 10.1038/nrc1209

E. Shaulian and M. Karin, AP-1 as a regulator of cell life and death, Nature Cell Biology, vol.4, issue.5, pp.131-136, 2002.
DOI : 10.1038/ncb0502-e131

J. Nevins, The Rb/E2F pathway and cancer. Human molecular genetics 10, pp.699-703, 2001.
DOI : 10.1093/hmg/10.7.699

URL : https://academic.oup.com/hmg/article-pdf/10/7/699/9813636/100699.pdf

E. S. Knudsen and J. Y. Wang, Targeting the RB-pathway in cancer therapy Clinical cancer research: an official journal of the American Association for, Cancer Research, vol.16, pp.1094-1103, 2010.