C. A. Learn, Resistance to tyrosine kinase inhibition by mutant epidermal growth factor receptor variant III contributes to the neoplastic phenotype of glioblastoma multiforme, Clin. Cancer Res, vol.10, pp.3216-3224, 2004.

Z. Zhang, Pygo2 activates MDR1 expression and mediates chemoresistance in breast cancer via the Wnt/?-catenin pathway, Oncogene, vol.35, pp.4787-4797, 2016.

N. Martín-martín, Stratification and therapeutic potential of PML in metastatic breast cancer, Nat. Commun, vol.7, p.12595, 2016.

J. Audoux, DE-kupl: exhaustive capture of biological variation in RNAseq data through k-mer decomposition, Genome Biol, vol.18, p.243, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01728770

J. M. Kirk, Functional classification of long non-coding RNAs by k-mer content, Nat. Genet, vol.1, 2018.

R. Ounit, S. Wanamaker, T. J. Close, S. Lonardi, and . Clark, fast and accurate classification of metagenomic and genomic sequences using discriminative kmer0s, BMC Genom, vol.16, p.236, 2015.

F. P. Breitwieser, D. N. Baker, and S. L. Salzberg, KrakenUniq: confident and fast metagenomics classification using unique k-mer counts, Genome Biol, vol.19, p.198, 2018.
DOI : 10.1186/s13059-018-1568-0

URL : https://doi.org/10.1186/s13059-018-1568-0

Y. D. Sergeyev, D. E. Kvasov, and M. S. Mukhametzhanov, On the efficiency of nature-inspired metaheuristics in expensive global optimization with limited budget, Sci. Rep, vol.8, p.453, 2018.

S. Juzenas, A comprehensive, cell specific microRNA catalogue of human peripheral blood, Nucleic Acids Res, vol.45, pp.9290-9301, 2017.

A. Kozomara and S. Griffiths-jones, miRBase: annotating high confidence microRNAs using deep sequencing data, Nucleic Acids Res, vol.42, pp.68-73, 2014.
DOI : 10.1093/nar/gkt1181

URL : https://academic.oup.com/nar/article-pdf/42/D1/D68/3618976/gkt1181.pdf

C. M. Perou, Molecular portraits of human breast tumours, Nature, vol.406, pp.747-752, 2000.

K. A. Hoadley, Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer, Cell, vol.173, pp.291-304, 2018.

M. Maziveyi and S. K. Alahari, Breast cancer tumor suppressors: a special emphasis on novel protein nischarin, Cancer Res, vol.75, pp.4252-4259, 2015.

M. S. Hasim, C. Nessim, P. J. Villeneuve, B. C. Vanderhyden, and J. Dimitroulakos, Activating transcription factor 3 as a novel regulator of chemotherapy response in breast cancer, Transl. Oncol, vol.11, pp.988-998, 2018.

S. E. Gijn and . Van, TPX2/Aurora kinase A signaling as a potential therapeutic target in genomically unstable cancer cells, Oncogene, vol.1, 2018.

J. Choi, Loss of KLHL6 promotes diffuse large B-cell lymphoma growth and survival by stabilizing the mRNA decay factor roquin2, Nat. Cell Biol, vol.20, pp.586-596, 2018.

N. E. Solari, The NSL chromatin-modifying complex subunit KANSL2 regulates cancer stem-like properties in glioblastoma that contribute to tumorigenesis, Cancer Res, vol.76, pp.5383-5394, 2016.

V. V. Tatarskiy, Stability of the PHF10 subunit of PBAF signature module is regulated by phosphorylation: role of ?, TrCP. Sci. Rep, vol.7, p.5645, 2017.

M. P. Goetz, Tumor sequencing and patient-derived xenografts in the neoadjuvant treatment of breast cancer, J. Natl. Cancer Inst, vol.109, p.7, 2017.

S. J. Thomas, J. A. Snowden, M. P. Zeidler, and S. J. Danson, The role of JAK/ STAT signalling in the pathogenesis, prognosis and treatment of solid tumours, Br. J. Cancer, vol.113, pp.365-371, 2015.

R. T. Sapio, Inhibition of post-transcriptional steps in ribosome biogenesis confers cytoprotection against chemotherapeutic agents in a p53-dependent manner, Sci. Rep, vol.7, p.9041, 2017.

J. R. Podojil and S. D. Miller, Potential targeting of B7-H4 for the treatment of cancer, Immunol. Rev, vol.276, pp.40-51, 2017.

D. A. Landau, Locally disordered methylation forms the basis of intratumor methylome variation in chronic lymphocytic leukemia, Cancer Cell, vol.26, pp.813-825, 2014.

F. Krueger and S. R. Andrews, Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications, Bioinformatics, vol.27, pp.1571-1572, 2011.

H. Wang, Widespread plasticity in CTCF occupancy linked to DNA methylation, Genome Res, vol.22, pp.1680-1688, 2012.

T. Fleischer, DNA methylation at enhancers identifies distinct breast cancer lineages, Nat. Commun, vol.8, p.1379, 2017.

R. Lesurf, ORegAnno 3.0: a community-driven resource for curated regulatory annotation, Nucleic Acids Res, vol.44, pp.126-132, 2016.

S. F. Alhasan, Sulfatase-2: a prognostic biomarker and candidate therapeutic target in patients with pancreatic ductal adenocarcinoma, Br. J. Cancer, vol.115, pp.797-804, 2016.

S. D. Rosen and H. Lemjabbar-alaoui, Sulf-2: an extracellular modulator of cell signaling and a cancer target candidate, Expert Opin. Ther. Targets, vol.14, pp.935-949, 2010.

N. S. Lui, SULF2 expression is a potential diagnostic and prognostic marker in lung cancer, PLoS ONE, vol.11, p.148911, 2016.

G. Marçais and C. Kingsford, A fast, lock-free approach for efficient parallel counting of occurrences of k-mers, Bioinformatics, vol.27, pp.764-770, 2011.

L. Gonzalez-abril, F. J. Cuberos, F. Velasco, and J. A. Ortega, Ameva: an autonomous discretization algorithm, Expert Syst. Appl, vol.36, pp.5327-5332, 2009.

F. Pedregosa, Scikit-learn: machine learning in python, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00650905

J. Zhang, H. S. Chung, and B. J. Hu, Adaptive probabilities of crossover and mutation in genetic algorithms based on clustering technique, Proc. 2004 Congress on Evolutionary Computation, vol.2, pp.2280-2287, 2004.

S. Ravindran, A. B. Jambek, H. Muthusamy, and S. Neoh, A novel clinical decision support system using improved adaptive genetic algorithm for the assessment of fetal well-being, Comput. Math. Methods Med, p.283532, 2015.

M. Yan, Improved adaptive genetic algorithm with sparsity constraint applied to thermal neutron CT reconstruction of two-phase flow, Meas. Sci. Technol, vol.29, p.55404, 2018.