A. Poret and J. Boissel, An in silico target identification using Boolean network attractors: Avoiding pathological phenotypes, Comptes Rendus Biologies, vol.337, issue.12, pp.661-678, 2014.
DOI : 10.1016/j.crvi.2014.10.002

L. Michelle, N. Wynn, . Consul, D. Sofia, S. Merajver et al., Logic-based models in systems biology: a predictive and parameter-free network analysis method, Integrative Biology, vol.4, issue.11, pp.1323-1337, 2012.

K. Melody, J. Morris, . Saez-rodriguez, K. Peter, . Sorger et al., Logic-based models for the analysis of cell signaling networks, Biochemistry, issue.15, pp.493216-3224, 2010.

R. Albert and J. Thakar, Boolean modeling: a logic-based dynamic approach for understanding signaling and regulatory networks and for making useful predictions, Wiley Interdisciplinary Reviews: Systems Biology and Medicine, vol.13, issue.Suppl 1, pp.353-369, 2014.
DOI : 10.1016/j.mib.2010.04.003

R. Wang, A. Saadatpour, and R. Albert, Boolean modeling in systems biology: an overview of methodology and applications, Physical Biology, vol.9, issue.5, p.55001, 2012.
DOI : 10.1088/1478-3975/9/5/055001

J. Jaeger and N. Monk, Bioattractors: dynamical systems theory and the evolution of regulatory processes, The Journal of Physiology, vol.108, issue.11, pp.2267-2281, 2014.
DOI : 10.1073/pnas.1017017108

S. Cho, S. Park, H. Lee, H. Lee, and K. Cho, Attractor landscape analysis of colorectal tumorigenesis and its reversion, BMC Systems Biology, vol.5, issue.10, p.96, 2016.
DOI : 10.1038/nrm1493

X. Gan and R. Albert, Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation, BMC Systems Biology, vol.223, issue.1, p.78, 2016.
DOI : 10.1016/S0022-5193(03)00035-3

J. Davila-velderrain, C. Juan, and E. Martinez-garcia, Modeling the epigenetic attractors landscape: toward a post-genomic mechanistic understanding of development, Frontiers in Genetics, vol.6, p.160, 2015.
DOI : 10.3389/fgene.2015.00160

I. Crespo, M. Thanneer, W. Perumal, A. D. Jurkowski, and . Sol, Detecting cellular reprogramming determinants by differential stability analysis of gene regulatory networks, BMC Systems Biology, vol.7, issue.1, 2013.
DOI : 10.1137/0204007

F. Herman, . Fumia, L. Marcelo, and . Martins, Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes, PloS One, vol.8, issue.7, p.69008, 2013.

W. Cheng, T. Yang, and D. Anastassiou, Biomolecular Events in Cancer Revealed by Attractor Metagenes, PLoS Computational Biology, vol.12, issue.2, p.1002920, 2013.
DOI : 10.1371/journal.pcbi.1002920.s010

URL : https://doi.org/10.1371/journal.pcbi.1002920

P. Creixell, M. Erwin, J. T. Schoof, R. Erler, and . Linding, Navigating cancer network attractors for tumor-specific therapy, Nature Biotechnology, vol.12, issue.9, pp.842-848, 2012.
DOI : 10.1242/dmm.004077

URL : http://www.nature.com/nbt/journal/v30/n9/pdf/nbt.2345.pdf

H. Chu, D. Lee, and K. Cho, Precritical State Transition Dynamics in the Attractor Landscape of a Molecular Interaction Network Underlying Colorectal Tumorigenesis, PLOS ONE, vol.4, issue.4, p.140172, 2015.
DOI : 10.1371/journal.pone.0140172.s007

E. Remy, S. Rebouissou, C. Chaouiya, A. Zinovyev, F. Radvanyi et al., A Modeling Approach to Explain Mutually Exclusive and Co-Occurring Genetic Alterations in Bladder Tumorigenesis, Cancer Research, vol.75, issue.19, pp.4042-4052, 2015.
DOI : 10.1158/0008-5472.CAN-15-0602

URL : https://hal.archives-ouvertes.fr/hal-01285974

A. Garg, A. D. Cara, I. Xenarios, L. Mendoza, and G. D. Micheli, Synchronous versus asynchronous modeling of gene regulatory networks, Bioinformatics, vol.24, issue.17, pp.1917-1925, 2008.
DOI : 10.1093/bioinformatics/btn336

T. Szekely and K. Burrage, Stochastic simulation in systems biology, Computational and Structural Biotechnology Journal, vol.12, issue.20-21, pp.14-25, 2014.
DOI : 10.1016/j.csbj.2014.10.003

M. Buiatti and G. Longo, Randomness and multilevel interactions in biology, Theory in Biosciences, vol.31, issue.7, pp.139-158, 2013.
DOI : 10.1099/00221287-114-2-487

URL : http://arxiv.org/pdf/1104.1110

M. Ullah and O. Wolkenhauer, Stochastic approaches in systems biology, Wiley Interdisciplinary Reviews: Systems Biology and Medicine, vol.260, issue.4, pp.385-397, 2010.
DOI : 10.1007/978-1-4613-1161-4

G. Rivas, P. Allen, and . Minton, Macromolecular Crowding In Vitro , In Vivo , and In Between, Trends in Biochemical Sciences, vol.41, issue.11, 2016.
DOI : 10.1016/j.tibs.2016.08.013

N. Rescher, Many-Valued Logic, 1968.
DOI : 10.1007/978-94-017-3546-9_6

C. Mussel, M. Hopfensitz, A. Hans, and . Kestler, BoolNet???an R package for generation, reconstruction and analysis of Boolean networks, Bioinformatics, vol.26, issue.10, pp.1378-1380, 2010.
DOI : 10.1093/bioinformatics/btq124

A. Saadatpour, I. Albert, and R. Albert, Attractor analysis of asynchronous Boolean models of signal transduction networks, Journal of Theoretical Biology, vol.266, issue.4, pp.641-656, 2010.
DOI : 10.1016/j.jtbi.2010.07.022

A. Lotfi and . Zadeh, Fuzzy sets, Information and Control, vol.8, issue.3, pp.338-353, 1965.

P. Cairns, K. Tokino, Y. Eby, and D. Sidransky, Homozygous deletions of 9p21 in primary human bladder tumors detected by comparative multiplex polymerase chain reaction, Cancer Research, vol.54, issue.6, pp.1422-1424, 1994.

J. Joshua, . Meeks, A. Benedito, . Carneiro, G. Sachin et al., Genomic characterization of high-risk non-muscle invasive bladder cancer, Oncotarget, issue.46, p.775176, 2016.

E. Koutsogiannouli, G. Athanasios, . Papavassiliou, A. Nikolaos, and . Papanikolaou, Complexity in cancer biology: is systems biology the answer? Cancer Medicine, pp.164-177, 2013.

C. Koch, Modular Biological Complexity, Science, vol.6, issue.3, pp.531-532, 2012.
DOI : 10.1371/journal.pone.0017013

S. Yu, J. , and N. Bagheri, Multi-class and multi-scale models of complex biological phenomena, Current Opinion in Biotechnology, vol.39, pp.167-173, 2016.
DOI : 10.1016/j.copbio.2016.04.002

J. Walpole, J. A. Papin, M. Shayn, and . Peirce, Multiscale Computational Models of Complex Biological Systems, Annual Review of Biomedical Engineering, vol.15, issue.1, pp.137-154, 2013.
DOI : 10.1146/annurev-bioeng-071811-150104

J. Fisher and N. Piterman, The executable pathway to biological networks, Briefings in Functional Genomics, vol.9, issue.1, pp.79-92, 2010.
DOI : 10.1093/bfgp/elp054

E. Voit, G. Qi, and . Miller, Steps of Modeling Complex Biological Systems, Pharmacopsychiatry, vol.41, issue.S 01, pp.41-78, 2008.
DOI : 10.1055/s-2008-1080911

H. Peter and F. , Mathematical modeling of complex biological systems: from parts lists to understanding systems behavior, Alcohol Research & Health, vol.31, issue.1, p.49, 2008.

G. Christos, . Mihos, M. Andres, O. Pineda, and . Santana, Cardiovascular effects of statins, beyond lipid-lowering properties, Pharmacological Research, vol.88, pp.12-19, 2014.

C. Mary-schooling, . Shiu-lun-au-yeung, M. Gabriel, and . Leung, Why do statins reduce cardiovascular disease more than other lipid modulating therapies?, European Journal of Clinical Investigation, vol.60, issue.11, pp.441135-1140, 2014.
DOI : 10.1016/j.jacc.2012.09.017

A. Ingrid, C. L. Mayer, and . Arteaga, The pi3k/akt pathway as a target for cancer treatment, Annual Review of Medicine, vol.67, pp.11-28

T. Shen and S. Huang, The role of cdc25a in the regulation of cell proliferation and apoptosis. Anti-Cancer Agents in Medicinal Chemistry, pp.631-639, 2012.

A. Lavecchia, C. D. Giovanni, and E. Novellino, CDC25A and B Dual-Specificity Phosphatase Inhibitors: Potential Agents for Cancer Therapy, Current Medicinal Chemistry, vol.16, issue.15, pp.1831-1849, 2009.
DOI : 10.2174/092986709788186084

X. Xu, H. Yamamoto, G. Liu, Y. Ito, M. Chew-yee-ngan et al., Mitsugu Sekimoto, and Morito Monden. Cdc25a inhibition suppresses the growth and invasion of human hepatocellular carcinoma cells, International Journal of Molecular Medicine, vol.21, issue.2, pp.145-152, 2008.

S. Kar, M. Wang, W. Yao, J. Christopher, . Michejda et al., PM-20, a novel inhibitor of Cdc25A, induces extracellular signal-regulated kinase 1/2 phosphorylation and inhibits hepatocellular carcinoma growth in vitro and in vivo, Molecular Cancer Therapeutics, vol.5, issue.6, pp.1511-1519, 2006.
DOI : 10.1158/1535-7163.MCT-05-0485

A. Sherif, . Rostom, H. Mona, . Badr, A. Heba et al., Structure-based development of novel triazoles and related thiazolotriazoles as anticancer agents and cdc25a/b phosphatase inhibitors. synthesis, in vitro biological evaluation, molecular docking and in silico adme-t studies, European Journal of Medicinal Chemistry, vol.139, pp.263-279, 2017.

S. Masoumi-moghaddam, A. Amini, and D. L. Morris, The developing story of Sprouty and cancer, Cancer and Metastasis Reviews, vol.98, issue.17, pp.695-720, 2014.
DOI : 10.1073/pnas.171209998

S. Wang, Y. Zhao, A. Aguilar, D. Bernard, and C. Yang, Targeting the mdm2-p53 protein-protein interaction for new cancer therapy: progress and challenges. Cold Spring Harbor Perspectives in Medicine, p.26245, 2017.

G. Leone, J. Degregori, Z. Yan, L. Jakoi, S. Ishida et al., E2F3 activity is regulated during the cell cycle and is required for the induction of S??phase, Genes & Development, vol.12, issue.14, pp.2120-2130, 1998.
DOI : 10.1101/gad.12.14.2120

C. Billerey, D. Chopin, M. Aubriot-lorton, D. Ricol, S. Gil-diez-de-medina et al., Frequent FGFR3 Mutations in Papillary Non-Invasive Bladder (pTa) Tumors, The American Journal of Pathology, vol.158, issue.6, pp.1955-1959, 2001.
DOI : 10.1016/S0002-9440(10)64665-2

URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891972/pdf

P. Seshacharyulu, P. Moorthy, D. Ponnusamy, M. Haridas, . Jain et al., Targeting the EGFR signaling pathway in cancer therapy, Expert Opinion on Therapeutic Targets, vol.62, issue.3, pp.15-31, 2012.
DOI : 10.1002/ijc.10398

S. Nathalie, J. Dhomen, N. Mariadason, . Tebbutt, M. Andrew et al., Therapeutic targeting of the epidermal growth factor receptor in human cancer, Critical Reviews in Oncogenesis, vol.17, issue.1, p.2012

. Lotfi-asker and . Zadeh, Fuzzy logic, Computer, vol.21, issue.4, pp.83-93, 1988.

A. Poret, C. M. Sousa, and J. Boissel, Enhancing boolean networks with fuzzy operators and edge tuning, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01018236

K. Melody, J. Morris, . Saez-rodriguez, C. David, . Clarke et al., Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli, PLoS Computational Biology, vol.7, issue.3, p.1001099, 2011.

B. Bree, J. Aldridge, J. L. Saez-rodriguez, . Muhlich, K. Peter et al., Fuzzy logic analysis of kinase pathway crosstalk in tnf/egf/insulin-induced signaling, PLoS Computational Biology, vol.5, issue.4, p.1000340, 2009.

X. Zhu, M. Gerstein, and M. Snyder, Getting connected: analysis and principles of biological networks, Genes & Development, vol.21, issue.9, pp.1010-1024, 2007.
DOI : 10.1101/gad.1528707

F. Emmert-streib, M. Dehmer, and B. Haibe-kains, Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks, Frontiers in Cell and Developmental Biology, vol.28, issue.8, p.38, 2014.
DOI : 10.1093/bioinformatics/btr626