F. Crick and J. Watson, Molecular structure of nucleic acids, Nature, 1953.

A. Dunker, . Romero, E. Obradovic, and . Garner, Intrinsic protein disorder in complete genomes, Genome Informatics, 2000.

R. , E. , and S. Hemmingsen, Molecular chaperones : proteins essential for the biogenesis of some macromolecular structures. Trends in biochemical sciences, 1989.

H. Dyson, E. Peter, and . Wright, Intrinsically unstructured proteins and their functions, Nature Reviews Molecular Cell Biology, vol.278, issue.3, pp.197-208, 2005.
DOI : 10.1038/nrm1589

J. , R. , and G. Cook, Energetics of bacterial growth : balance of anabolic and catabolic reactions. Microbiological reviews, 1995.

Z. Wang, M. Gerstein, and . Snyder, RNA-Seq: a revolutionary tool for transcriptomics, Nature Reviews Genetics, vol.328, issue.1, 2009.
DOI : 10.1038/nrg2484

C. Anfinsen and E. Haber, Studies on the reduction and re-formation of protein disulfide bonds, J Biol Chem, 1961.

C. Anfinsen, Principles that Govern the Folding of Protein Chains, Science, vol.181, issue.4096, 1973.
DOI : 10.1126/science.181.4096.223

S. Piana, K. Lindorff-larsen, E. David, and . Shaw, How Robust Are Protein Folding Simulations with Respect to Force Field Parameterization?, Biophysical Journal, vol.100, issue.9, pp.47-49, 2011.
DOI : 10.1016/j.bpj.2011.03.051

S. Piana, G. Alexander, P. Donchev, . Robustelli, E. David et al., Water Dispersion Interactions Strongly Influence Simulated Structural Properties of Disordered Protein States, The Journal of Physical Chemistry B, vol.119, issue.16, pp.5113-5123, 2015.
DOI : 10.1021/jp508971m

E. David and . Shaw, Anton, a special-purpose machine for molecular dynamics simulation, Commun. ACM, vol.51, issue.7, p.91, 2008.

D. Joseph, . Bryngelson, G. Peter, and . Wolynes, Spin glasses and the statistical mechanics of protein folding, PNAS, vol.84, issue.21, pp.7524-7528, 1987.

B. Derrida, Random-energy model: An exactly solvable model of disordered systems, Physical Review B, vol.24, issue.5, p.2613, 1981.
DOI : 10.1103/PhysRevB.24.2613

R. Mélin, N. Li, C. Wingreen, and . Tang, Designability, thermodynamic stability, and dynamics in protein folding: A lattice model study, The Journal of Chemical Physics, vol.110, issue.2
DOI : 10.1063/1.478168

R. Mclaughlin, J. Frank, A. Poelwijk, . Raman, S. Walraj et al., The spatial architecture of protein function and adaptation, Nature, vol.13, issue.7422, pp.138-142, 2012.
DOI : 10.1038/nature11500

O. Claus, J. L. Wilke, C. Wang, . Ofria, E. Richard et al., Evolution of digital organisms at high mutation rates leads to survival of the flattest, Nature, issue.6844, pp.412331-333, 2001.

G. Sergio, . Peisajovich, S. Dan, and . Tawfik, Protein engineers turned evolutionists, Nature methods, vol.4, issue.12, pp.991-994, 2007.

M. Monique and . Tirion, Large amplitude elastic motions in proteins from a single-parameter, atomic analysis, Phys. Rev. Lett, vol.77, issue.9, p.1905, 1996.

I. Bahar, A. R. Atilgan, and B. Erman, Direct evaluation of thermal fluctuations in proteins using a singleparameter harmonic potential. Folding and Design, pp.173-181, 1997.

T. Haliloglu, B. Bahar, and . Erman, Gaussian Dynamics of Folded Proteins, Physical Review Letters, vol.79, issue.16, pp.3090-3093, 1997.
DOI : 10.1103/PhysRevLett.79.3090

M. Hemery and O. Rivoire, Evolution of sparsity and modularity in a model of protein allostery, Physical Review E, vol.91, issue.4, p.42704, 2015.
DOI : 10.1103/PhysRevE.91.042704

URL : https://hal.archives-ouvertes.fr/hal-01301839

S. Mahajan and Y. Sanejouand, On the relationship between low-frequency normal modes and the large-scale conformational changes of proteins, Archives of Biochemistry and Biophysics, vol.567, issue.C, pp.59-65, 2015.
DOI : 10.1016/j.abb.2014.12.020

W. Zheng and S. Doniach, A comparative study of motor-protein motions by using a simple elastic-network model, Proceedings of the National Academy of Sciences, vol.100, issue.23, pp.13253-13258, 2003.
DOI : 10.1073/pnas.2235686100

F. Piazza and Y. Sanejouand, Long-range energy transfer in proteins, Physical Biology, vol.6, issue.4, p.46014, 2009.
DOI : 10.1088/1478-3975/6/4/046014

URL : https://hal.archives-ouvertes.fr/hal-00431838

G. Cohen, Regulation of Enzyme Activity in Microorganisms, Annual Review of Microbiology, vol.19, issue.1, 1965.
DOI : 10.1146/annurev.mi.19.100165.000541

J. Monod, J. Wyman, and J. Changeux, On the nature of allosteric transitions: A plausible model, Journal of Molecular Biology, vol.12, issue.1, pp.88-118, 1965.
DOI : 10.1016/S0022-2836(65)80285-6

A. Garcia-pino, S. Balasubramanian, L. Wyns, E. Gazit, H. De-greve et al., Allostery bibliographie 121

J. Rhoda, . Hawkins, C. Tom, and . Mcleish, Coarse-Grained Model Of Entropic Allostery, Phys. Rev. Lett, vol.93, issue.9, p.98104, 2004.

N. Hesam, . Motlagh, O. James, J. Wrabl, . Li et al., The ensemble nature of allostery, Nature, vol.508, issue.7496, pp.331-339, 2014.

D. Ferreiro, J. Hegler, and E. Komives, On the role of frustration in the energy landscapes of allosteric proteins, Proceedings of the National Academy of Sciences, vol.108, issue.9, 2011.
DOI : 10.1073/pnas.1018980108

L. Thomas, D. Rodgers, . Burnell, D. Phil, E. Townsend et al., DD PT : a comprehensive toolbox for the analysis of protein motion, BMC Bioinformatics, vol.14, issue.1, p.183, 2013.

L. Thomas, . Rodgers, D. Philip, D. Townsend, . Burnell et al., Modulation of Global Low-Frequency Motions Underlies Allosteric Regulation : Demonstration in CRP/FNR Family Transcription Factors, PLoS Biol, vol.11, issue.9, p.1001651, 2013.

W. B. Provine, The Origins of Theoretical Population Genetics., Systematic Zoology, vol.21, issue.1, 1971.
DOI : 10.2307/2412271

C. Darwin, On the origin of species by means of natural selection, J. Murray, p.1859
DOI : 10.5962/bhl.title.24329

R. Barrangou, C. Fremaux, H. Deveau, M. Richards, P. Boyaval et al., CRISPR Provides Acquired Resistance Against Viruses in Prokaryotes, Science, vol.315, issue.5819, pp.3151709-1712, 2007.
DOI : 10.1126/science.1138140

I. Bjedov, O. Tenaillon, B. Gerard, V. Souza, E. Denamur et al., Stress-Induced Mutagenesis in Bacteria, Science, vol.300, issue.5624, pp.3001404-1409, 2003.
DOI : 10.1126/science.1082240

O. Rivoire and S. Leibler, A model for the generation and transmission of variations in evolution, Proceedings of the National Academy of Sciences, vol.111, issue.19, pp.1940-1949, 2014.
DOI : 10.1073/pnas.1323901111

URL : https://hal.archives-ouvertes.fr/hal-00998067

K. Vetsigian, C. Woese, and N. Goldenfeld, Collective evolution and the genetic code. arXiv, q-bio, 2006.

F. Jacob, Evolution and tinkering, Science, vol.196, issue.4295, pp.1161-1166, 1977.
DOI : 10.1126/science.860134

O. Rivoire and S. Leibler, The Value of Information for Populations in Varying Environments, Journal of Statistical Physics, vol.68, issue.2???3, pp.1124-1166, 2011.
DOI : 10.1007/s10955-011-0166-2

URL : https://hal.archives-ouvertes.fr/hal-00961034

S. Gould and R. Lewontin, The Spandrels of San Marco and the Panglossian Paradigm: A Critique of the Adaptationist Programme, Proceedings of the Royal Society B: Biological Sciences, vol.205, issue.1161, pp.581-598, 1161.
DOI : 10.1098/rspb.1979.0086

A. Richard, C. A. Neher, . Russell, I. Boris, and . Shraiman, Predicting evolution from the shape of genealogical trees, eLife, vol.3, 2014.

D. Jesse, C. O. Bloom, . Wilke, H. Frances, C. Arnold et al., Stability and the evolvability of function in a model protein, Biophysical Journal, vol.86, issue.5, pp.2758-2764, 2004.

S. J. Gould, Wonderful Life : The Burgess Shale and the Nature of History, 1989.

G. Ivan, J. Szendro, J. Franke, G. Arjan, J. Visser et al., Predictability of evolution depends nonmonotonically on population size, pp.571-576, 2013.

R. Doeke, S. Hekstra, and . Leibler, Contingency and Statistical Laws in Replicate Microbial Closed Ecosystems, Cell, vol.149, issue.5, pp.1164-1173, 2012.

M. Mitchell, H. John, S. Holland, and . Forrest, When will a genetic algorithm outperform hill climbing ?, NIPS Advances in Neural Information Processing Systems, pp.51-58, 1994.

B. Miller and D. Goldberg, Genetic Algorithms, Selection Schemes, and the Varying Effects of Noise, Evolutionary Computation, vol.4, issue.2, 1996.
DOI : 10.1162/evco.1996.4.2.113

Q. Pham, Competitive evolution : a natural approach to operator selection. Progress in evolutionary computation, pp.49-60, 1995.

J. H. Holland, Adaptation in natural and artificial systems, 1992.

M. Mitchell, An Introduction to Genetic Algorithms, 1998.

S. Nolfi and D. Floreano, Evolutionary Robotics, 2000.
DOI : 10.1007/978-3-319-32552-1_76

M. Daniel, S. Weinreich, . Sindi, A. Richard, and . Watson, Finding the boundary between evolutionary basins of attraction , and implications for Wright's fitness landscape analogy, J. Stat. Mech, issue.01, pp.2013-01001, 2013.

B. Batut, P. David, S. Parsons, G. Fischer, C. Beslon et al., In silico experimental evolution: a tool to test evolutionary scenarios, BMC Bioinformatics, vol.14, issue.Suppl 15, p.11, 2013.
DOI : 10.1016/j.jtbi.2006.09.005

URL : https://hal.archives-ouvertes.fr/hal-00873232

E. V. Koonin, The logic of chance, the nature and origin of biological evolution, 2011.

K. Christof, M. Biebricher, and . Eigen, The error threshold, Virus Research, vol.107, issue.2, pp.117-127, 2005.

C. Chothia and . Proteins, One thousand families for the molecular biologist, Nature, vol.357, issue.6379, 1992.
DOI : 10.1038/357543a0

H. Taketomi, Y. Ueda, and N. , STUDIES ON PROTEIN FOLDING, UNFOLDING AND FLUCTUATIONS BY COMPUTER SIMULATION, International Journal of Peptide and Protein Research, vol.6, issue.6, 1975.
DOI : 10.1111/j.1399-3011.1975.tb02465.x

P. Williams, D. Pollock, and R. Goldstein, Evolution of functionality in lattice proteins, Journal of Molecular Graphics and Modelling, vol.19, issue.1, pp.150-156, 2001.
DOI : 10.1016/S1093-3263(00)00125-X

K. Dill, Theory for the folding and stability of globular proteins, Biochemistry, vol.24, issue.6, 1985.
DOI : 10.1021/bi00327a032

S. Miyazawa and R. Jernigan, Estimation of effective interresidue contact energies from protein crystal structures: quasi-chemical approximation, Macromolecules, vol.18, issue.3, 1985.
DOI : 10.1021/ma00145a039

E. Shakhnovich, A. Farztdinov, M. Gutin, and . Karplus, Protein folding bottlenecks: A lattice Monte Carlo simulation, Physical Review Letters, vol.67, issue.12, p.1665, 1991.
DOI : 10.1103/PhysRevLett.67.1665

H. Li, R. Helling, C. Tang, and N. Wingreen, Emergence of Preferred Structures in a Simple Model of Protein Folding, Science, vol.273, issue.5275, pp.666-669, 1996.
DOI : 10.1126/science.273.5275.666

E. Bornberg-bauer and H. Chan, Modeling evolutionary landscapes: Mutational stability, topology, and superfunnels in sequence space, PNAS, 1999.
DOI : 10.1073/pnas.96.19.10689

Y. Xia and M. Levitt, Roles of mutation and recombination in the evolution of protein thermodynamics, PNAS, 2002.
DOI : 10.1073/pnas.162097799

G. Trinquier and Y. Sanejouand, New proteinlike properties of cubic lattice models, Physical Review E, vol.59, issue.1, 1999.
DOI : 10.1103/PhysRevE.59.942

L. Jeremy, E. I. England, and . Shakhnovich, Structural Determinant of Protein Designability, Phys. Rev. Lett, vol.90, issue.21, p.218101, 2003.

R. Helling, . Li, . Mélin, N. Miller, and . Wingreen, The designability of protein structures, Journal of Molecular Graphics and Modelling, vol.19, issue.1, 2001.
DOI : 10.1016/S1093-3263(00)00137-6

B. Konstantin, . Zeldovich, N. Igor, E. I. Berezovsky, and . Shakhnovich, Physical Origins of Protein Superfamilies, Journal of Molecular Biology, vol.357, issue.4, pp.1335-1343, 2006.

E. Shakhnovich and A. Gutin, Engineering of stable and fast-folding sequences of model proteins., Proceedings of the National Academy of Sciences, vol.90, issue.15, pp.7195-7199, 1993.
DOI : 10.1073/pnas.90.15.7195

S. Ramanathan and E. Shakhnovich, Statistical mechanics of proteins with ??????evolutionary selected?????? sequences, Physical Review E, vol.50, issue.2, p.1303, 1994.
DOI : 10.1103/PhysRevE.50.1303

S. Saito, T. Sasai, and . Yomo, Evolution of the folding ability of proteins through functional selection, Proceedings of the National Academy of Sciences, vol.94, issue.21, p.9411324, 1997.
DOI : 10.1073/pnas.94.21.11324

W. Fontana and P. Schuster, Shaping Space: the Possible and the Attainable in RNA Genotype???phenotype Mapping, Journal of Theoretical Biology, vol.194, issue.4, pp.491-515, 1998.
DOI : 10.1006/jtbi.1998.0771

S. Dalal, L. Balasubramanian, and . Regan, Protein alchemy : changing b-sheet into a-helix, Nature Structural & Molecular Biology, 1997.

A. Sakata, K. Hukushima, and K. Kaneko, Funnel Landscape and Mutational Robustness as a Result of Evolution under Thermal Noise, Physical Review Letters, vol.102, issue.14, p.148101, 2009.
DOI : 10.1103/PhysRevLett.102.148101

I. Berezovsky and E. Shakhnovich, Physics and evolution of thermophilic adaptation, Proceedings of the National Academy of Sciences, vol.102, issue.36, pp.12742-12747, 2005.
DOI : 10.1073/pnas.0503890102

A. Schug and W. Wenzel, An Evolutionary Strategy for All-Atom Folding of the 60-Amino-Acid Bacterial Ribosomal Protein L20, Biophysical Journal, vol.90, issue.12, pp.4273-4280, 2006.
DOI : 10.1529/biophysj.105.070409

P. Benjamin, . Blackburne, D. Jonathan, and . Hirst, Evolution of functional model proteins, J. Chem. Phys, vol.115, issue.4, p.1935, 2001.

M. Heo, E. Kang, and . Shakhnovich, Emergence of species in evolutionary ???simulated annealing???, Proceedings of the National Academy of Sciences, vol.106, issue.6, pp.18638-18643, 2009.
DOI : 10.1073/pnas.0809852106

V. Tozzini, Coarse-grained models for proteins, Current Opinion in Structural Biology, vol.15, issue.2, pp.144-150, 2005.
DOI : 10.1016/j.sbi.2005.02.005

P. Shenkin and B. Erman, Information-theoretical entropy as a measure of sequence variability, Proteins: Structure, Function, and Genetics, vol.339, issue.4, 1991.
DOI : 10.1002/prot.340110408

M. Socolich, W. Steve, . Lockless, P. William, H. Russ et al., Evolutionary information for specifying a protein fold, Nature, vol.9, issue.7058, pp.437512-518, 2005.
DOI : 10.1016/0263-7855(96)00009-4

M. Weigt, R. White, J. Szurmant, T. Hoch, and . 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

W. Bialek and R. Ranganathan, Rediscovering the power of pairwise interactions. arXiv, q-bio, 2007.

F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, S. Debora et al., Directcoupling analysis of residue coevolution captures native contacts across many protein families, 2011.

W. Steve, R. Lockless, and . Ranganathan, Evolutionarily conserved pathways of energetic connectivity in protein families, Science, vol.286, issue.5438, pp.295-299, 1999.

. Stanley, Random matrix approach to cross correlations in financial data, Phys. Rev. E, vol.65, issue.6, p.66126, 2002.

N. Halabi, O. Rivoire, S. Leibler, and R. Ranganathan, Protein Sectors: Evolutionary Units of Three-Dimensional Structure, Cell, vol.138, issue.4, pp.774-786, 2009.
DOI : 10.1016/j.cell.2009.07.038

O. Rivoire, Elements of Coevolution in Biological Sequences, Physical Review Letters, vol.110, issue.17, 2013.
DOI : 10.1103/PhysRevLett.110.178102

URL : https://hal.archives-ouvertes.fr/hal-00961061

O. Rivoire, A. Kimberly, R. Reynolds, and . Ranganathan, The Structure of Evolutionary Constraints in Proteins

A. Kimberly, . Reynolds, N. Richard, R. Mclaughlin, and . Ranganathan, Hot Spots for Allosteric Regulation on Protein Surfaces, Cell, vol.147, issue.7, pp.1564-1575, 2011.

N. Raichman, R. Segev, and E. , Evolvable hardware : genetic search in a physical realm. Physica A : Statistical Mechanics and its Applications, pp.265-285, 2003.

R. Calabretta, . Nolfi, G. Parisi, and . Wagner, Duplication of Modules Facilitates the Evolution of Functional Specialization, Artificial Life, vol.256, issue.1, 2000.
DOI : 10.2307/2410639

N. Kashtan and U. Alon, Spontaneous evolution of modularity and network motifs, Proceedings of the National Academy of Sciences, vol.102, issue.39, pp.13773-13778, 2005.
DOI : 10.1073/pnas.0503610102

A. Evan, H. Variano, and . Lipson, Networks, Dynamics, and Modularity, Phys. Rev. Lett, vol.92, issue.18, p.188701, 2004.

M. Lynch, The Origins of Eukaryotic Gene Structure, Molecular Biology and Evolution, vol.23, issue.2, pp.450-468, 2005.
DOI : 10.1093/molbev/msj050

F. Santiago, . Elena, E. Richard, and . Lenski, Microbial genetics : Evolution experiments with microorganisms : the dynamics and genetic bases of adaptation, Nat Rev Genet, vol.4, issue.6, pp.457-469, 2003.

P. Romero and F. Arnold, Exploring protein fitness landscapes by directed evolution, Nature Reviews Molecular Cell Biology, vol.125, issue.12, pp.866-876, 2009.
DOI : 10.1038/nrm2805

U. Alon, N. Kashtan, and E. Noor, Varying environments can speed up evolution, PNAS, vol.104, issue.34, pp.13711-13716, 2007.

T. Friedlander, A. Mayo, U. Tlusty, and . Alon, Mutation Rules and the Evolution of Sparseness and Modularity in Biological Systems, PLoS ONE, vol.261, issue.8, 2013.
DOI : 10.1371/journal.pone.0070444.s003

A. Thompson, Hadware Evolution : Automatic design of electronic circuits in reconfigurable hardware by artificial evolution, 1998.

P. François, Evolving phenotypic networks in silico, Seminars in Cell & Developmental Biology, vol.35, pp.90-97, 2014.
DOI : 10.1016/j.semcdb.2014.06.012

E. Van-nimwegen, J. Crutchfield, and M. Huynen, Neutral evolution of mutational robustness, Proceedings of the National Academy of Sciences, vol.96, issue.17, pp.9716-9720, 1999.
DOI : 10.1073/pnas.96.17.9716

A. Wagner and . Robustness, Robustness, evolvability, and neutrality, FEBS Letters, vol.188, issue.8, pp.1772-1778, 2005.
DOI : 10.1016/j.febslet.2005.01.063

P. Gros, L. Nagard, and O. Tenaillon, The Evolution of Epistasis and Its Links With Genetic Robustness, Complexity and Drift in a Phenotypic Model of Adaptation, Genetics, vol.182, issue.1, pp.277-293, 2009.
DOI : 10.1534/genetics.108.099127

A. Jeremy, . Draghi, L. Todd, . Parsons, P. Günter et al., Mutational robustness can facilitate adaptation, Nature, vol.463, issue.7279, pp.353-355, 2010.

A. Wagner, Robustness and evolvability: a paradox resolved, Proceedings of the Royal Society B: Biological Sciences, vol.46, issue.17, pp.91-100, 1630.
DOI : 10.1073/pnas.96.17.9716

M. Rorick and G. Wagner, Protein Structural Modularity and Robustness Are Associated with Evolvability, Genome Biology and Evolution, vol.3, issue.0, pp.456-475, 2011.
DOI : 10.1093/gbe/evr046

S. Kryazhimskiy, J. Tka?ik, and . Plotkin, The dynamics of adaptation on correlated fitness landscapes, Proceedings of the National Academy of Sciences, vol.106, issue.44, pp.18638-18643, 2009.
DOI : 10.1073/pnas.0905497106

A. Dawid, J. Daniel, M. Kiviet, . Kogenaru, . Marjon-de-vos et al., Multiple peaks and reciprocal sign epistasis in an empirically determined genotype-phenotype landscape, Chaos: An Interdisciplinary Journal of Nonlinear Science, vol.20, issue.2, p.26105, 2010.
DOI : 10.1063/1.3453602

URL : https://hal.archives-ouvertes.fr/hal-00867970

S. Wright, The roles of mutation, inbreeding, crossbreeding and selection in evolution, pp.356-366, 1932.

M. Darin, . Taverna, A. Richard, and . Goldstein, Why are proteins marginally stable ?, Proteins : Structure, Function, and Bioinformatics, vol.46, issue.1, pp.105-109, 2001.

H. David, . Wolpert, G. William, and . Macready, No free lunch theorems for optimization, Evolutionary Computation IEEE Transactions on, vol.1, issue.1, pp.67-82, 1997.

A. Mitchell, H. Gal, B. Romano, A. Groisman, E. Yona et al., Adaptive prediction of environmental changes by microorganisms, Nature, issue.7252, pp.460220-224, 2009.

J. Hastad, Almost optimal lower bounds for small depth circuits, Proceedings of the eighteenth annual ACM symposium on Theory of computing , STOC '86, pp.6-20, 1986.
DOI : 10.1145/12130.12132

E. Geoffrey, S. Hinton, Y. Osindero, and . Teh, A fast learning algorithm for deep belief nets, Neural computation, vol.18, issue.7, pp.1527-1554, 2006.

Y. Bengio, J. Louradour, R. Collobert, and J. Weston, Curriculum learning, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, pp.41-48, 2009.
DOI : 10.1145/1553374.1553380

I. Goodfellow, H. Lee, V. Quoc, A. Le, . Saxe et al., Measuring invariances in deep networks, Advances in neural information processing systems, pp.646-654, 2009.

I. Junier and O. Rivoire, Synteny in Bacterial Genomes : Inference, Organization and Evolution. arXiv, qbio .GN, 2013.

H. John and . Gillespie, Natural selection for within-generation variance in offspring number, Genetics, vol.76, issue.3, pp.601-606, 1974.

S. Gavrilets and J. Gravner, Percolation on the Fitness Hypercube and the Evolution of Reproductive Isolation, Journal of Theoretical Biology, vol.184, issue.1, pp.51-64, 1997.
DOI : 10.1006/jtbi.1996.0242

V. Mustonen and M. Lässig, From fitness landscapes to seascapes: non-equilibrium dynamics of selection and adaptation, Trends in Genetics, vol.25, issue.3, pp.111-119, 2009.
DOI : 10.1016/j.tig.2009.01.002

S. K. Mills and J. H. Beatty, The Propensity Interpretation of Fitness, Philosophy of Science, vol.46, issue.2, pp.263-286, 1979.
DOI : 10.1086/288865

T. H. Berlin and M. Kac, The spherical model of a ferromagnet . The physical review, pp.1-15, 1952.