X. Wu, T. Zhou, J. Zhu, B. Zhang, I. Georgiev et al., Focused Evolution of HIV-1 Neutralizing Antibodies Revealed by Structures and Deep Sequencing, Science, vol.333, issue.6049, pp.1593-1602, 2011.
DOI : 10.1126/science.1207532

K. Krawczyk, X. Liu, T. Baker, J. Shi, and C. Deane, Improving B-cell epitope prediction and its application to global antibody-antigen docking, Bioinformatics, vol.30, issue.16, p.190, 2014.
DOI : 10.1093/bioinformatics/btu190

V. Potapov, M. Cohen, and G. Schreiber, Assessing computational methods for predicting protein stability upon mutation: good on average but not in the details, Protein Engineering Design and Selection, vol.22, issue.9, pp.553-560, 2009.
DOI : 10.1093/protein/gzp030

J. Benichou, R. Ben-hamo, Y. Louzoun, and S. Efroni, Rep-Seq: uncovering the immunological repertoire through next-generation sequencing, Immunology, vol.37, issue.Suppl, pp.183-191, 2012.
DOI : 10.1111/j.1365-2567.2011.03527.x

J. Weinstein, N. Jiang, R. White, D. Fisher, and S. Quake, High-Throughput Sequencing of the Zebrafish Antibody Repertoire, Science, vol.324, issue.5928, 2009.
DOI : 10.1126/science.1170020

K. Larimore, M. Mccormick, H. Robins, and P. Greenberg, Shaping of human germline IgH repertoires revealed by deep sequencing, The Journal of Immunology, vol.189, issue.6, p.22865917, 2012.

T. Mora, A. Walczak, W. Bialek, and C. Callan, Maximum entropy models for antibody diversity, Proceedings of the National Academy of Sciences, vol.107, issue.12, pp.5405-5410, 2010.
DOI : 10.1073/pnas.1001705107

A. Murugan, T. Mora, A. Walczak, and C. Callan, Statistical inference of the generation probability of T-cell receptors from sequence repertoires, Proceedings of the National Academy of Sciences, vol.109, issue.40, pp.16161-16166, 2012.
DOI : 10.1073/pnas.1212755109

Y. Elhanati, A. Murugan, C. Callan, T. Mora, and A. Walczak, Quantifying selection in immune receptor repertoires, Proceedings of the National Academy of Sciences, vol.111, issue.27, pp.9875-9880, 2014.
DOI : 10.1073/pnas.1409572111

D. De-juan, F. Pazos, and A. Valencia, Emerging methods in protein co-evolution, Nature Reviews Genetics, vol.485, issue.4, p.23458856, 2013.
DOI : 10.1371/journal.pgen.1000570

R. Finn, A. Bateman, J. Clements, C. Pl, R. Eberhardt et al., Pfam: the protein families database, Nucleic Acids Research, vol.42, issue.D1, pp.222-230, 2014.
DOI : 10.1093/nar/gkt1223
URL : https://hal.archives-ouvertes.fr/hal-01294685

A. Lapedes, B. Giraud, L. Liu, and G. Stormo, Correlated Mutations in Models of Protein Sequences: Phylogenetic and Structural Effects. Lecture Notes-Monograph Series, Statistics in Molecular Biology and Genetics, vol.33, pp.236-256, 1999.

M. Weigt, R. White, H. Szurmant, J. Hoch, and T. Hwa, Identification of direct residue contacts in protein-protein interaction by message passing, Proceedings of the National Academy of Sciences, vol.106, issue.1, pp.67-72, 2009.
DOI : 10.1073/pnas.0805923106

F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks et al., Direct-coupling analysis of residue coevolution captures native contacts across many protein families, Proceedings of the National Academy of Sciences, vol.108, issue.49, pp.1293-1301, 2011.
DOI : 10.1073/pnas.1111471108

D. Marks, L. Colwell, R. Sheridan, T. Hopf, A. Pagnani et al., Protein 3D Structure Computed from Evolutionary Sequence Variation, PLoS ONE, vol.437, issue.12, p.22163331
DOI : 10.1371/journal.pone.0028766.s022

S. Balakrishnan, H. Kamisetty, J. Carbonell, S. Lee, and C. Langmead, Learning generative models for protein fold families, Proteins: Structure, Function, and Bioinformatics, vol.34, issue.4, 2011.
DOI : 10.1002/prot.22934

M. Ekeberg, C. Lövkvist, Y. Lan, M. Weigt, and E. Aurell, Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models, Physical Review E, vol.87, issue.1, pp.12707-12717, 2013.
DOI : 10.1103/PhysRevE.87.012707

C. Feinauer, M. Skwark, A. Pagnani, and E. Aurell, Improving Contact Prediction along Three Dimensions, PLoS Computational Biology, vol.24, issue.10, p.25299132
DOI : 10.1371/journal.pcbi.1003847.s002

D. Jones, D. Buchan, D. Cozzetto, and M. Pontil, PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments, Bioinformatics, vol.28, issue.2, p.22101153, 2012.
DOI : 10.1093/bioinformatics/btr638

C. Baldassi, M. Zamparo, C. Feinauer, A. Procaccini, R. Zecchina et al., Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners, PLoS ONE, vol.36, issue.3, p.24663061
DOI : 10.1371/journal.pone.0092721.s001
URL : https://hal.archives-ouvertes.fr/hal-01344551

P. Parameswaran, Y. Liu, K. Roskin, K. Jackson, V. Dixit et al., Convergent Antibody Signatures in Human Dengue, Cell Host & Microbe, vol.13, issue.6, pp.691-700, 2013.
DOI : 10.1016/j.chom.2013.05.008

K. Jackson, Y. Liu, K. Roskin, J. Glanville, R. Hoh et al., Human Responses to Influenza Vaccination Show Seroconversion Signatures and Convergent Antibody Rearrangements, Cell Host & Microbe, vol.16, issue.1, pp.105-114, 2014.
DOI : 10.1016/j.chom.2014.05.013

J. Trück, M. Ramasamy, J. Galson, R. Rance, J. Parkhill et al., Identification of Antigen-Specific B Cell Receptor Sequences Using Public Repertoire Analysis, The Journal of Immunology, vol.194, issue.1, pp.252-261, 2015.
DOI : 10.4049/jimmunol.1401405

J. Mann, J. Barton, A. Ferguson, S. Omarjee, B. Walker et al., The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing, PLoS Computational Biology, vol.86, issue.8, p.25102049
DOI : 10.1371/journal.pcbi.1003776.s002

M. Figliuzzi, H. Jacquier, A. Schug, O. Tenaillon, and M. Weigt, Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1, Molecular Biology and Evolution, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01284957

M. Lefranc, Nomenclature of the Human Immunoglobulin Heavy (IGH) Genes, Experimental and Clinical Immunogenetics, vol.18, issue.2, pp.100-116, 2001.
DOI : 10.1159/000049189

J. Ye, N. Ma, T. Madden, and J. Ostell, IgBLAST: an immunoglobulin variable domain sequence analysis tool, Nucleic Acids Research, vol.41, issue.W1, p.382, 2013.
DOI : 10.1093/nar/gkt382

A. Chailyan, A. Tramontano, and P. Marcatili, A database of immunoglobulins with integrated tools: DIGIT. Nucleic acids research, p.806, 2011.

P. Marcatili, P. Olimpieri, A. Chailyan, and A. Tramontano, Erratum: Antibody modeling using the Prediction of ImmunoGlobulin Structure (PIGS) web server, Nature Protocols, vol.10, issue.4, pp.2771-2783, 2014.
DOI : 10.1038/nprot0415-644e

H. Shirai, C. Prades, R. Vita, P. Marcatili, B. Popovic et al., Antibody informatics for drug discovery, BBA)-Proteins and Proteomics, pp.2002-2015, 2014.
DOI : 10.1016/j.bbapap.2014.07.006
URL : https://hal.archives-ouvertes.fr/hal-01088585

A. Honegger and A. Pluèckthun, Yet Another Numbering Scheme for Immunoglobulin Variable Domains: An Automatic Modeling and Analysis Tool, Journal of Molecular Biology, vol.309, issue.3, pp.657-670, 2001.
DOI : 10.1006/jmbi.2001.4662

M. Bailly-bechet, S. Bradde, A. Braunstein, A. Flaxman, L. Foini et al., Clustering with shallow trees, Journal of Statistical Mechanics: Theory and Experiment, vol.2009, issue.12, pp.12010-12020, 2009.
DOI : 10.1088/1742-5468/2009/12/P12010
URL : https://hal.archives-ouvertes.fr/hal-00539395

M. Lefranc, V. Giudicelli, C. Ginestoux, J. Jabado-michaloud, G. Folch et al., IMGT 1 , the international ImMunoGeneTics information system 1, Nucleic acids research, vol.37, issue.1, 2009.

J. Schymkowitz, J. Borg, F. Stricher, R. Nys, F. Rousseau et al., The FoldX web server: an online force field. Nucleic acids research, pp.382-388, 2005.

B. Webb and A. Sali, Comparative protein structure modeling using Modeller. Current protocols in bioinformatics, pp.5-6, 2014.

S. Eddy, A NEW GENERATION OF HOMOLOGY SEARCH TOOLS BASED ON PROBABILISTIC INFERENCE, Genome Informatics 2009, pp.205-211, 2009.
DOI : 10.1142/9781848165632_0019

R. Finn, J. Clements, and S. Eddy, HMMER web server: interactive sequence similarity searching, Nucleic Acids Research, vol.39, issue.suppl, pp.29-37, 2011.
DOI : 10.1093/nar/gkr367

R. Neher and B. Shraiman, Competition between recombination and epistasis can cause a transition from allele to genotype selection, Proceedings of the National Academy of Sciences, vol.106, issue.16, pp.6866-6871, 2009.
DOI : 10.1073/pnas.0812560106

A. Mayer, V. Balasubramanian, T. Mora, and A. Walczak, How a well-adapted immune system is organized. arXiv preprint arXiv:14076888, 2014.

S. Becattini, D. Latorre, F. Mele, M. Foglierini, D. Gregorio et al., Functional heterogeneity of human memory CD4+ T cell clones primed by pathogens or vaccines, Science, vol.347, issue.6220, pp.400-406, 2015.
DOI : 10.1126/science.1260668