P. Agius, A. Arvey, W. Chang, W. S. Noble, L. et al., High Resolution Models of Transcription Factor-DNA Affinities Improve In Vitro and In Vivo Binding Predictions, PLoS Computational Biology, vol.11, issue.9, 2010.
DOI : 10.1371/journal.pcbi.1000916.s001

T. Alam, Y. A. Medvedeva, H. Jia, J. B. Brown, L. Lipovich et al., Promoter Analysis Reveals Globally Differential Regulation of Human Long Non-Coding RNA and Protein-Coding Genes, PLoS ONE, vol.464, issue.10, 2014.
DOI : 10.1371/journal.pone.0109443.s016

B. Alipanahi, A. Delong, M. T. Weirauch, and B. J. Frey, Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning, Nature Biotechnology, vol.13, issue.8, pp.831-838, 2015.
DOI : 10.1126/science.1162327

P. Antoniou, J. Holub, C. S. Iliopoulos, B. Melichar, and P. Peterlongo, Finding Common Motifs with Gaps Using Finite Automata, Proceedings of the 11th International Conference on Implementation and Application of Automata CIAA'06, pp.69-77, 2006.
DOI : 10.1007/11812128_8

URL : https://hal.archives-ouvertes.fr/hal-00619849

G. Badis, M. F. Berger, A. A. Philippakis, S. Talukder, A. R. Gehrke et al., Diversity and Complexity in DNA Recognition by Transcription Factors, Science, vol.324, issue.5935, pp.1720-1723, 2009.
DOI : 10.1126/science.1162327

T. L. Bailey, M. Boden, F. A. Buske, M. Frith, C. E. Grant et al., MEME SUITE: tools for motif discovery and searching, Nucleic Acids Research, vol.37, issue.Web Server, pp.202-208, 2009.
DOI : 10.1093/nar/gkp335

T. L. Bailey and C. Elkan, The value of prior knowledge in discovering motifs with MEME, Proc. Int. Conf. Intell. Syst. Mol. Biol, vol.3, pp.21-29, 1995.

Y. Barash, G. Elidan, N. Friedman, and T. Kaplan, Modeling dependencies in protein-DNA binding sites, Proceedings of the seventh annual international conference on Computational molecular biology , RECOMB '03, pp.28-37, 2003.
DOI : 10.1145/640075.640079

D. P. Bartel, MicroRNAs: Target Recognition and Regulatory Functions, Cell, vol.136, issue.2, pp.215-233, 2009.
DOI : 10.1016/j.cell.2009.01.002

S. K. Behura and D. W. Severson, Bidirectional Promoters of Insects: Genome-Wide Comparison, Evolutionary Implication and Influence on Gene Expression, Journal of Molecular Biology, vol.427, issue.2, pp.521-536, 2015.
DOI : 10.1016/j.jmb.2014.11.008

I. Ben-gal, A. Shani, A. Gohr, J. Grau, S. Arviv et al., Identification of transcription factor binding sites with variable-order Bayesian networks Universal protein-binding microarrays for the comprehensive characterization of the DNA-binding specificities of transcription factors, Bioinformatics Nat. Protoc, vol.21, issue.4, pp.2657-2666, 0195.

V. Boeva, A. Lermine, C. Barette, C. Guillouf, E. Barillot et al., Nebula--a web-server for advanced ChIP-seq data analysis, Bioinformatics, vol.28, issue.19, pp.2517-2519, 2006.
DOI : 10.1093/bioinformatics/bts463

A. P. Boyle, E. L. Hong, M. Hariharan, Y. Cheng, M. A. Schaub et al., Annotation of functional variation in personal genomes using RegulomeDB, Genome Research, vol.22, issue.9, pp.1790-1797, 2012.
DOI : 10.1101/gr.137323.112

P. Burda, P. Laslo, and T. Stopka, The role of PU.1 and GATA-1 transcription factors during normal and leukemogenic hematopoiesis, Leukemia, vol.72, issue.7, pp.1249-1257, 2010.
DOI : 10.1182/blood-2005-07-3068

D. S. Chekmenev, C. Haid, and A. E. Kel, P-Match: transcription factor binding site search by combining patterns and weight matrices, Nucleic Acids Research, vol.33, issue.Web Server, pp.432-437, 2005.
DOI : 10.1093/nar/gki441

L. J. Chin, E. Ratner, S. Leng, R. Zhai, S. Nallur et al., A SNP in a let-7 microRNA Complementary Site in the KRAS 3' Untranslated Region Increases Non-Small Cell Lung Cancer Risk, Cancer Research, vol.68, issue.20, pp.8535-8540, 2008.
DOI : 10.1158/0008-5472.CAN-08-2129

G. Cuellar-partida, F. A. Buske, R. C. Mcleay, T. Whitington, W. S. Noble et al., Epigenetic priors for identifying active transcription factor binding sites, Bioinformatics, vol.28, issue.1, pp.56-62, 2012.
DOI : 10.1093/bioinformatics/btr614

T. Derrien, J. Estellé, M. Sola, S. Knowles, D. G. Raineri et al., Fast Computation and Applications of Genome Mappability, PLoS ONE, vol.39, issue.Suppl 1, 2012.
DOI : 10.1371/journal.pone.0030377.t002

URL : https://hal.archives-ouvertes.fr/inserm-00664289

I. V. Deyneko, A. E. Kel, O. V. Kel-margoulis, E. V. Deineko, E. Wingender et al., MatrixCatch - a novel tool for the recognition of composite regulatory elements in promoters, BMC Bioinformatics, vol.14, issue.1, pp.241-251, 2013.
DOI : 10.1093/hmg/ddp532

R. Eggeling, A. Gohr, J. Keilwagen, M. Mohr, S. Posch et al., On the Value of Intra-Motif Dependencies of Human Insulator Protein CTCF, PLoS ONE, vol.24, issue.1, 2014.
DOI : 10.1371/journal.pone.0085629.s013

P. J. Farnham, E. Fazius, V. Shelest, E. A. Shelest, G. Robertson et al., Insights from genomic profiling of transcription factors SiTaR: a novel tool for transcription factor binding site prediction FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets, Nat. Rev. Genet. Bioinformatics Bioinformatics Nucleic Acids Res, vol.10, issue.41, pp.605-616, 2008.

M. C. Frith, Y. Fu, L. Yu, J. Chen, U. Hansen et al., Detection of functional DNA motifs via statistical over-representation, Nucleic Acids Research, vol.32, issue.4, pp.1372-1381, 2003.
DOI : 10.1093/nar/gkh299

S. Georgiev, A. P. Boyle, K. Jayasurya, X. Ding, S. Mukherjee et al., Evidence-ranked motif identification, Genome Biology, vol.11, issue.2, 2010.
DOI : 10.1186/gb-2010-11-2-r19

R. Gordân, N. Shen, I. Dror, T. Zhou, J. Horton et al., Genomic Regions Flanking E-Box Binding Sites Influence DNA Binding Specificity of bHLH Transcription Factors through DNA Shape, Cell Reports, vol.3, issue.4, pp.1093-1104, 2013.
DOI : 10.1016/j.celrep.2013.03.014

D. U. Gorkin, D. Lee, X. Reed, C. Fletez-brant, S. L. Bessling et al., Integration of ChIP-seq and machine learning reveals enhancers and a predictive regulatory sequence vocabulary in melanocytes, Genome Research, vol.22, issue.11, pp.2290-2301, 2012.
DOI : 10.1101/gr.139360.112

C. E. Grant, J. Johnson, T. L. Bailey, N. , and W. S. , MCAST: scanning for cis-regulatory motif clusters, 2015.

J. Grau, I. Ben-gal, S. Posch, and I. Grosse, VOMBAT: prediction of transcription factor binding sites using variable order Bayesian trees, Nucleic Acids Research, vol.34, issue.Web Server, pp.529-533, 2006.
DOI : 10.1093/nar/gkl212

J. Grau, S. Posch, I. Grosse, J. And-keilwagen, O. V. Grinchuk et al., A general approach for discriminative de novo motif discovery from high-throughput data. Nucleic Acids Res. 41, e197. doi: 10.C/gkt831 Sense-antisense gene-pairs in breast cancer and associated pathological pathways, Oncotarget, vol.6, pp.42197-422216255, 2013.

N. Guillon, F. Tirode, V. Boeva, A. Zynovyev, E. Barillot et al., The Oncogenic EWS-FLI1 Protein Binds In Vivo GGAA Microsatellite Sequences with Potential Transcriptional Activation Function, PLoS ONE, vol.7, issue.1, 2009.
DOI : 10.1371/journal.pone.0004932.s003

Y. Guo, S. Mahony, G. , and D. K. , High Resolution Genome Wide Binding Event Finding and Motif Discovery Reveals Transcription Factor Spatial Binding Constraints, PLoS Computational Biology, vol.8, issue.8, 2012.
DOI : 10.1371/journal.pcbi.1002638.s026

S. Gupta, J. A. Stamatoyannopoulos, T. L. Bailey, N. , and W. S. , Quantifying similarity between motifs, Genome Biology, vol.8, issue.2, pp.24-34, 2007.
DOI : 10.1186/gb-2007-8-2-r24

Y. Halperin, C. Linhart, I. Ulitsky, and R. Shamir, Allegro: Analyzing expression and sequence in concert to discover regulatory programs, Nucleic Acids Research, vol.37, issue.5, pp.1566-1579, 2009.
DOI : 10.1093/nar/gkn1064

S. Heinz, C. Benner, N. Spann, E. Bertolino, Y. C. Lin et al., Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities, Molecular Cell, vol.38, issue.4, pp.576-589, 2010.
DOI : 10.1016/j.molcel.2010.05.004

C. Herrmann, B. Van-de-sande, D. Potier, and S. Aerts, i-cisTarget: an integrative genomics method for the prediction of regulatory features and cis-regulatory modules Identifying DNA and protein patterns with statistically significant alignments of multiple sequences, Nucleic Acids Res. Bioinformatics, vol.15, pp.563-577, 1999.

D. T. Holloway, M. Kon, and C. Delisi, Integrating genomic data to predict transcription factor binding, Genome Inform, vol.16, pp.83-94, 2005.

J. Holub, The finite automata approaches in stringology, pp.386-401, 2012.

M. Hu, J. Yu, J. M. Taylor, A. M. Chinnaiyan, and Q. , On the detection and refinement of transcription factor binding sites using ChIP-Seq data, Nucleic Acids Research, vol.38, issue.7, pp.2154-2167, 1180.
DOI : 10.1093/nar/gkp1180

H. Imrichová, G. Hulselmans, Z. Kalender-atak, D. Potier, and S. Aerts, i-cisTarget 2015 update: generalized cis-regulatory enrichment analysis in human, mouse and fly, Nucleic Acids Research, vol.43, issue.W1, pp.57-64, 2015.
DOI : 10.1093/nar/gkv395

C. Iseli, G. Ambrosini, P. Bucher, and C. V. Jongeneel, Indexing Strategies for Rapid Searches of Short Words in Genome Sequences, PLoS ONE, vol.32, issue.6, 2007.
DOI : 10.1371/journal.pone.0000579.g005

C. Jia, M. B. Carson, Y. Wang, Y. Lin, L. et al., A New Exhaustive Method and Strategy for Finding Motifs in ChIP-Enriched Regions, PLoS ONE, vol.35, issue.1, 2014.
DOI : 10.1371/journal.pone.0086044.t007

B. Jiang, M. Q. Zhang, and X. Zhang, OSCAR: One-class SVM for accurate recognition of cis-elements, Bioinformatics, vol.23, issue.21, pp.2823-2828, 2007.
DOI : 10.1093/bioinformatics/btm473

D. S. Johnson, A. Mortazavi, R. M. Myers, and B. Wold, Genome-Wide Mapping of in Vivo Protein-DNA Interactions, Science, vol.316, issue.5830, pp.1497-1502, 2007.
DOI : 10.1126/science.1141319

S. Kasinathan, G. A. Orsi, G. E. Zentner, K. Ahmad, and S. Henikoff, High-resolution mapping of transcription factor binding sites on native chromatin, Epigenetics & Chromatin, vol.6, issue.Suppl 1, pp.203-209, 2014.
DOI : 10.1186/1756-8935-6-S1-P114

J. Keilwagen and J. Grau, Varying levels of complexity in transcription factor binding motifs, Nucleic Acids Research, vol.43, issue.18, pp.119-119, 2015.
DOI : 10.1093/nar/gkv577

H. Kim, J. Kim, H. Selby, D. Gao, T. Tong et al., A short survey of computational analysis methods in analysing ChIP-seq data, Human Genomics, vol.5, issue.2, pp.117-123, 2011.
DOI : 10.1038/ng1400

R. J. Klose, S. Cooper, A. M. Farcas, N. P. Blackledge, and N. Brockdorff, Chromatin Sampling???An Emerging Perspective on Targeting Polycomb Repressor Proteins, PLoS Genetics, vol.27, issue.8, 2013.
DOI : 10.1371/journal.pgen.1003717.g003

K. Kozlov, V. V. Gursky, I. V. Kulakovskiy, A. Dymova, M. Samsonova et al., Analysis of functional importance of binding sites in the Drosophila gap gene network model 13):S7. doi: 10.1186/1471- 2164-16-S13-S7 Kulakovskiy, I From binding motifs in ChIP-Seq data to improved models of transcription factor binding sites Deep and wide digging for binding motifs in ChIP-Seq data, BMC Genomics J. Bioinform. Comput. Biol. Bioinformatics, vol.16, issue.26, pp.2622-2623, 2010.

I. V. Kulakovskiy, Y. A. Medvedeva, U. Schaefer, A. S. Kasianov, I. E. Vorontsov et al., HOCOMOCO: a comprehensive collection of human transcription factor binding sites models, Nucleic Acids Research, vol.41, issue.D1, pp.195-202, 2013.
DOI : 10.1093/nar/gks1089

A. T. Kwon, D. J. Arenillas, R. W. Hunt, and W. W. Wasserman, oPOSSUM-3: Advanced Analysis of Regulatory Motif Over-Representation Across Genes or ChIP-Seq Datasets, G3: Genes|Genomes|Genetics, vol.2, issue.9, pp.987-1002, 2012.
DOI : 10.1534/g3.112.003202

S. G. Landt, G. K. Marinov, A. Kundaje, P. Kheradpour, F. Pauli et al., ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia, Genome Research, vol.22, issue.9, pp.1813-1831, 2012.
DOI : 10.1101/gr.136184.111

A. Lihu, ¸. S. Holban, P. J. Collins, N. D. Trinklein, Y. Fu et al., A review of ensemble methods for de novo motif discovery in ChIP-Seq data, Briefings in Bioinformatics, vol.16, issue.6, pp.964-973, 2007.
DOI : 10.1093/bib/bbv022

C. Linhart, Y. Halperin, and R. Shamir, Transcription factor and microRNA motif discovery: The Amadeus platform and a compendium of metazoan target sets, Genome Research, vol.18, issue.7, pp.1180-1189, 2008.
DOI : 10.1101/gr.076117.108

P. V. Loo, S. Aerts, B. Thienpont, B. D. Moor, Y. Moreau et al., ModuleMiner -improved computational detection of cis-regulatory modules: are there different modes of gene regulation in embryonic development and adult tissues?, Genome Biol. Genome Biol, vol.12, issue.9, pp.10-1186, 2008.

X. Ma, A. Kulkarni, Z. Zhang, Z. Xuan, R. Serfling et al., A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information, Nucleic Acids Research, vol.40, issue.7, pp.50-50, 1135.
DOI : 10.1093/nar/gkr1135

P. Machanick, T. L. Bailey, S. Mahony, and P. V. Benos, MEME-ChIP: motif analysis of large DNA datasets STAMP: a web tool for exploring DNA-binding motif similarities Construction of minimal deterministic finite automata from biological motifs, Bioinformatics Nucleic Acids Res. Theor. Comput. Sci, vol.27, issue.412, pp.1696-1697, 2007.

T. Marschall and S. And-rahmann, Probabilistic arithmetic automata and their application to pattern matching statistics Available online at, Combinatorial Pattern Matching Lecture Notes in Computer Science, pp.95-106978, 1007.

T. T. Marstrand, J. Frellsen, I. Moltke, M. Thiim, E. Valen et al., Asap: A Framework for Over-Representation Statistics for Transcription Factor Binding Sites, PLoS ONE, vol.33, issue.2, 2008.
DOI : 10.1371/journal.pone.0001623.s001

A. Mathelier, O. Fornes, D. J. Arenillas, C. Chen, G. Denay et al., JASPAR 2016: a major expansion and update of the openaccess database of transcription factor binding profiles The next generation of transcription factor binding site prediction, Nucleic Acids Res. PLoS Comput. Biol, vol.44, 2013.

V. Matys, O. V. Kel-margoulis, E. Fricke, I. Liebich, S. Land et al., TRANSFAC(R) and its module TRANSCompel(R): transcriptional gene regulation in eukaryotes, Nucleic Acids Research, vol.34, issue.90001, pp.108-110, 2006.
DOI : 10.1093/nar/gkj143

R. C. Mcleay and T. L. Bailey, Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data, BMC Bioinformatics, vol.11, issue.1, pp.165-175, 2010.
DOI : 10.1186/1471-2105-11-165

R. C. Mcleay, C. J. Leat, T. L. Bailey, C. Meckbach, R. Tacke et al., Tissue-specific prediction of directly regulated genes PC-TraFF: identification of potentially collaborating transcription factors using pointwise mutual information, Bioinformatics BMC Bioinformatics, vol.27, issue.16, pp.2354-2360, 2011.

A. Medina-rivera, M. Defrance, O. Sand, C. Herrmann, J. A. Castro-mondragon et al., RSAT 2015: Regulatory Sequence Analysis Tools, Nucleic Acids Research, vol.43, issue.W1, pp.50-56, 2013.
DOI : 10.1093/nar/gkv362

G. Navarro and M. Raffinot, Flexible Pattern Matching in Strings: Practical On-line Search Algorithms for Texts and Biological Sequences, 2002.
DOI : 10.1017/CBO9781316135228

A. A. Nikulova, A. V. Favorov, R. A. Sutormin, V. J. Makeev, and A. A. Mironov, CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation, Nucleic Acids Research, vol.40, issue.12, 2012.
DOI : 10.1093/nar/gks235

URL : https://hal.archives-ouvertes.fr/hal-00696900

A. R. Oliphant, C. J. Brandl, and K. Struhl, Defining the sequence specificity of DNA-binding proteins by selecting binding sites from random-sequence oligonucleotides: analysis of yeast GCN4 protein., Molecular and Cellular Biology, vol.9, issue.7, pp.2944-2949, 1989.
DOI : 10.1128/MCB.9.7.2944

M. Pachkov, I. Erb, N. Molina, and E. Van-nimwegen, SwissRegulon: a database of genome-wide annotations of regulatory sites, Nucleic Acids Research, vol.35, issue.Database, pp.127-131, 2007.
DOI : 10.1093/nar/gkl857

V. Politi, G. Perini, S. Trazzi, A. Pliss, I. Raska et al., CENP-C binds the alpha-satellite DNA in vivo at specific centromere domains, 2002.

G. Ramsingh, D. C. Koboldt, M. Trissal, K. B. Chiappinelli, T. Wylie et al., Available online at: http://jcs.biologists.org/content Complete characterization of the microRNAome in a patient with acute myeloid leukemia, J. Cell. Sci. Blood, vol.11511, issue.116, pp.2317-2327, 2010.

J. E. Reid, K. J. Evans, N. Dyer, L. Wernisch, and S. Ott, Variable structure motifs for transcription factor binding sites, BMC Genomics, vol.11, issue.1, pp.30-40, 2010.
DOI : 10.1186/1471-2164-11-30

H. S. Rhee and B. F. Pugh, Comprehensive Genome-wide Protein-DNA Interactions Detected at Single-Nucleotide Resolution, Cell, vol.147, issue.6, 2011.
DOI : 10.1016/j.cell.2011.11.013

M. Ridinger-saison, V. Boeva, P. Rimmelé, I. Kulakovskiy, I. Gallais et al., Spi-1/PU.1 activates transcription through clustered DNA occupancy in erythroleukemia, Nucleic Acids Research, vol.40, issue.18, pp.8927-8941, 2012.
DOI : 10.1093/nar/gks659

N. Riggi, B. Knoechel, S. M. Gillespie, E. Rheinbay, G. Boulay et al., EWS-FLI1??Utilizes Divergent Chromatin Remodeling Mechanisms to Directly Activate or Repress Enhancer Elements in Ewing Sarcoma, Cancer Cell, vol.26, issue.5, pp.668-681, 2014.
DOI : 10.1016/j.ccell.2014.10.004

P. Rimmelé, J. Komatsu, P. Hupé, C. Roulin, E. Barillot et al., Spi-1/PU.1 Oncogene Accelerates DNA Replication Fork Elongation and Promotes Genetic Instability in the Absence of DNA Breakage, Cancer Research, vol.70, issue.17, pp.6757-6766, 2010.
DOI : 10.1158/0008-5472.CAN-09-4691

T. D. Schneider and R. M. Stephens, Sequence logos: a new way to display consensus sequences, Nucleic Acids Research, vol.18, issue.20, 1990.
DOI : 10.1093/nar/18.20.6097

A. Sebastian and B. Contreras-moreira, footprintDB: a database of transcription factors with annotated cis elements and binding interfaces, Bioinformatics, vol.30, issue.2, pp.258-265, 2014.
DOI : 10.1093/bioinformatics/btt663

V. Shelest, D. Albrecht, and E. Shelest, DistanceScan: a tool for promoter modeling, Bioinformatics, vol.26, issue.11, pp.1460-1462, 2010.
DOI : 10.1093/bioinformatics/btq132

X. M. Shi, H. C. Blair, X. Yang, J. M. Mcdonald, C. et al., Tandem repeat of C/EBP binding sites mediates PPARgamma2 gene transcription in glucocorticoid-induced adipocyte differentiation, 3%3C518::AID- JCB18%3E3.0.CO, pp.518-527, 2000.

S. R. Starick, J. Ibn-salem, M. Jurk, C. Hernandez, M. I. Love et al., ChIP-exo signal associated with DNA-binding motifs provides insight into the genomic binding of the glucocorticoid receptor and cooperating transcription factors, Genome Research, vol.25, issue.6, pp.825-835, 2015.
DOI : 10.1101/gr.185157.114

G. D. Stormo, DNA binding sites: representation and discovery, Bioinformatics, vol.16, issue.1, pp.16-23, 2000.
DOI : 10.1093/bioinformatics/16.1.16

S. Sun, H. Guns, T. Fierro, A. C. Thorrez, L. Nijssen et al., ModuleDigger: an itemset mining framework for the detection of cis-regulatory modules Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection, BMC Bioinformatics Nucleic Acids Res, vol.10, issue.40, pp.90-90, 2012.

N. T. Tran and C. Huang, A survey of motif finding Web tools for detecting binding site motifs in ChIP-Seq data, Biology Direct, vol.9, issue.1, pp.4-10, 2014.
DOI : 10.1038/nbt1053

I. E. Vorontsov, I. V. Kulakovskiy, and V. J. Makeev, The Polycomb group protein EZH2 directly controls DNA methylation Jaccard index based similarity measure to compare transcription factor binding site models, Nature Algorithms Mol. Biol, vol.439, issue.8, pp.871-87423, 2013.

J. Wang, J. Zhuang, S. Iyer, X. Lin, T. W. Whitfield et al., Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors, Genome Research, vol.22, issue.9, pp.1798-1812, 2012.
DOI : 10.1101/gr.139105.112

L. D. Ward and M. Kellis, HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease, Nucleic Acids Research, vol.44, issue.D1, pp.877-881, 1340.
DOI : 10.1093/nar/gkv1340

T. Wasson and A. J. Hartemink, An ensemble model of competitive multi-factor binding of the genome, Genome Research, vol.19, issue.11, 2009.
DOI : 10.1101/gr.093450.109

M. T. Weirauch, A. Cote, R. Norel, M. Annala, Y. Zhao et al., Evaluation of methods for modeling transcription factor sequence specificity, Nature Biotechnology, vol.23, issue.2, pp.126-134, 2013.
DOI : 10.1093/nar/gkr1055

E. G. Wilbanks and M. T. Facciotti, Evaluation of Algorithm Performance in ChIP-Seq Peak Detection, PLoS ONE, vol.24, issue.7, 2010.
DOI : 10.1371/journal.pone.0011471.s014

C. Yang, E. Bolotin, T. Jiang, F. M. Sladek, and E. Martinez, Prevalence of the initiator over the TATA box in human and yeast genes and identification of DNA motifs enriched in human TATA-less core promoters, Gene, vol.389, issue.1, pp.52-65, 2007.
DOI : 10.1016/j.gene.2006.09.029

D. Yue, H. Liu, and Y. Huang, Survey of Computational Algorithms for MicroRNA Target Prediction, Current Genomics, vol.10, issue.7, pp.478-492, 2009.
DOI : 10.2174/138920209789208219

F. Zambelli, G. Pesole, and G. Pavesi, Pscan: finding over-represented transcription factor binding site motifs in sequences from co-regulated or co-expressed genes, Nucleic Acids Research, vol.37, issue.Web Server, pp.247-252, 2009.
DOI : 10.1093/nar/gkp464

Y. Zhang, T. Liu, C. A. Meyer, J. Eeckhoute, D. S. Johnson et al., Model-based Analysis of ChIP-Seq (MACS), Genome Biology, vol.9, issue.9, pp.137-147, 2008.
DOI : 10.1186/gb-2008-9-9-r137

Y. Zhao, S. Ruan, M. Pandey, and G. D. Stormo, Improved Models for Transcription Factor Binding Site Identification Using Nonindependent Interactions, Genetics, vol.191, issue.3, pp.781-790, 2012.
DOI : 10.1534/genetics.112.138685

Y. Zhao and G. D. Stormo, Quantitative analysis demonstrates most transcription factors require only simple models of specificity, Nature Biotechnology, vol.11, issue.6, pp.480-483, 2011.
DOI : 10.1371/journal.pcbi.1000916

J. Zheng, J. Wu, and Z. Sun, An approach to identify over-represented cis-elements in related sequences, Nucleic Acids Research, vol.31, issue.7, 1995.
DOI : 10.1093/nar/gkg287

S. Zhong, X. He, B. , and Z. , Predicting tissue specific transcription factor binding sites, BMC Genomics, vol.14, issue.1, pp.796-806, 2013.
DOI : 10.1089/cmb.2012.0253