M. Basseville and I. V. Nikiforov, Detection of Abrupt Changes: Theory and Applications, 1993.

J. Baudry, C. Maugis, and B. Michel, Slope heuristics: overview and implementation, Statistics and Computing, vol.6, issue.2, p.455470, 2012.
DOI : 10.1007/s11222-011-9236-1

URL : https://hal.archives-ouvertes.fr/hal-00461639

R. Bellman, On the approximation of curves by line segments using dynamic programming, Communications of the ACM, vol.4, issue.6, p.284, 1961.
DOI : 10.1145/366573.366611

H. Cho and P. Fryzlewicz, Multiple-change-point detection for high dimensional time series via sparsied binary segmentation, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.77, issue.2, p.475507, 2015.
DOI : 10.1111/rssb.12079

URL : http://arxiv.org/abs/1611.08639

A. Cleynen, S. Dudoit, and S. Robin, Comparing Segmentation Methods for Genome Annotation Based on RNA-Seq Data, Journal of Agricultural, Biological, and Environmental Statistics, vol.30, issue.1, 2013.
DOI : 10.1007/s13253-013-0159-5

URL : https://hal.archives-ouvertes.fr/hal-01197620

J. R. Dixon, S. Selvaraj, F. Yue, A. Kim, Y. Li et al., Topological domains in mammalian genomes identied by analysis of chromatin interactions, Nature, vol.485, issue.7398, p.376380, 2012.

L. Horvath and M. Huskova, Change-point detection in panel data, Journal of Time Series Analysis, vol.20, issue.4, p.631648, 2012.
DOI : 10.1111/j.1467-9892.2012.00796.x

M. Jirak, Uniform change point tests in high dimension, The Annals of Statistics, vol.43, issue.6, pp.2015-24512483
DOI : 10.1214/15-AOS1347SUPP

S. Kay, Fundamentals of statistical signal processing: detection theory, 1993.

R. Killick, P. Fearnhead, and I. A. Eckley, Optimal Detection of Changepoints With a Linear Computational Cost, Journal of the American Statistical Association, vol.63, issue.500, p.15901598, 2012.
DOI : 10.1080/01621459.2012.737745

E. L. Lehmann and H. J. D-'abrera, Nonparametrics: statistical methods based on ranks, 2006.

C. Lévy-leduc, M. Delattre, T. Mary-huard, and S. Robin, Two-dimensional segmentation for analyzing HiC data, Bioinformatics, vol.30, issue.17, p.386392, 2014.

C. Lévy-leduc and F. Roue, Detection and localization of change-points in highdimensional network trac data, Ann. Applied Statist, vol.3, issue.2, p.637662, 2009.

E. Lieberman-aiden, N. L. Van-berkum, L. Williams, M. Imakaev, T. Ragoczy et al., Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome, Science, vol.326, issue.5950, p.289293, 2009.
DOI : 10.1126/science.1181369

A. Lung-yut-fong, C. Lévy-leduc, and O. Cappé, Homogeneity and change-point detection tests for multivariate data using rank statistics, Journal de la Société Française de Statistique, vol.156, issue.4, p.133162, 2015.
URL : https://hal.archives-ouvertes.fr/hal-00607410

D. S. Matteson and N. A. James, A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data, Journal of the American Statistical Association, vol.6, issue.505, p.334345, 2014.
DOI : 10.1111/j.1541-0420.2006.00662.x

F. Picard, S. Robin, M. Lavielle, C. Vaisse, and J. Daudin, A statistical approach for array CGH data analysis, BMC Bioinformatics, vol.6, issue.1, p.27, 2005.
DOI : 10.1186/1471-2105-6-27

URL : https://hal.archives-ouvertes.fr/hal-00427846

J. G. Szekely and L. M. Rizzo, Hierarchical Clustering via Joint Between-Within Distances: Extending Ward's Minimum Variance Method, Journal of Classification, vol.22, issue.2, p.151183, 2005.
DOI : 10.1007/s00357-005-0012-9

A. Tartakovsky, B. Rozovskii, R. Blazek, and H. Kim, A novel approach to detection of intrusions in computer networks via adaptive sequential and batch-sequential changepoint detection methods, IEEE Trans. Signal Process, vol.54, issue.3372, p.3382, 2006.

J. Vert and K. Bleakley, Fast detection of multiple change-points shared by many signals using group LARS, Advances in Neural Information Processing Systems 23, p.23432351, 2010.