Publications

Research articles: 

1. Meynard-Piganeau, B., Feinauer, C., Weigt, M., Walczak, A. M., & Mora, T. (2024). TULIP: A transformer-based unsupervised language model for interacting peptides and T cell receptors that generalizes to unseen epitopes. Proc. Natl. Acad. Sci. 121(24), e2316401121.

2. Calvanese, F., Lambert, C. N., Nghe, P., Zamponi, F., & Weigt, M. (2024). Towards parsimonious generative modeling of RNA families. Nucleic Acids Research, gkae289.

3. Meynard-Piganeau, B., Fabbri, C., Weigt, M., Pagnani, A., & Feinauer, C. (2023). Generating Interacting Protein Sequences using Domain-to-Domain Translation. Bioinformatics 39 (7), btad401.

4. Gandarilla-Perez, C. A., Pinilla, S., Bitbol, A. F., & Weigt, M. (2023). Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins. PLOS Computational Biology 19 (3), e1011010.

5. Ciarella, S., Trinquier, J., Weigt, M., & Zamponi, F. (2023). Machine-learning-assisted Monte Carlo fails at sampling computationally hard problems. Machine Learning: Science and Technology, 4, 010501.

6. Patteson, J. B., Fortinez, C. M., Putz, A. T., Rodriguez-Rivas, J., Bryant III, L. H., Adhikari, K., ... & Li, B. (2022). Structure and Function of a Dehydrating Condensation Domain in Nonribosomal Peptide Biosynthesis. Journal of the American Chemical Society, 144(31), 14057-14070.

7. Vigué, L., Croce, G., Petitjean, M., Ruppé, E., Tenaillon, O., & Weigt, M. (2022). Deciphering polymorphism in 61,157 Escherichia coli genomes via epistatic sequence landscapes. Nature Communications 13, 4030.

8. Rodriguez-Rivas, J., Croce, G., Muscat, M., & Weigt, M. (2022). Epistatic models predict mutable sites in SARS-CoV-2 proteins and epitopes. Proc. Natl. Acad. Sci. 119 (4) e2113118119.

9. Bisardi, M., Rodriguez-Rivas, J., Zamponi, F., & Weigt, M. (2021). Modeling sequence-space exploration and emergence of epistatic signals in protein evolution.  Molecular Biology and Evolution msab321.

10. Trinquier, J., Uguzzoni, G., Pagnani, A., Zamponi, F., & Weigt, M. (2021). Efficient generative modeling of protein sequences using simple autoregressive models. Nature Communications 12, 5800.

11. Muntoni, A. P., Pagnani, A., Weigt, M., & Zamponi, F. (2021). adabmDCA: Adaptive Boltzmann machine learning for biological sequences. BMC Bioinformatics, 22:528.

12. Barrat-Charlaix, P., Muntoni, A. P., Shimagaki, K., Weigt, M., & Zamponi, F. (2021). Sparse generative modeling via parameter reduction of Boltzmann machines: application to protein-sequence families. Physical Review E, 104(2), 024407.

13. Rodriguez Horta, E., Lage, A., Weigt, M. and Barrat-Charlaix, P. (2021). Global multivariate model learning from hierarchically correlated data. J. Stat. Mech. 073501.

14. Rodriguez Horta, E., & Weigt, M. (2021). On the effect of phylogenetic correlations in coevolution-based contact prediction in proteins. PLOS Computational Biology, 17(5), e1008957.

15. Muntoni, A. P., Pagnani, A., Weigt, M., & Zamponi, F. (2020). Aligning biological sequences by exploiting residue conservation and coevolution. Physical Review E, 102(6), 062409.

16. Russ, W.P., Figliuzzi, M., Stocker, C., Barrat-Charlaix, P., Socolich, M., Kast, P., Hilvert, D., Monasson, R., Cocco, S., Weigt*, M. and Ranganathan*, R., 2020. An evolution-based model for designing chorismate mutase enzymes. Science, 369(6502), pp.440-445. (* corr authors)

17. Muscat M, Croce G, Sarti E, Weigt M (2020) FilterDCA: Interpretable supervised contact prediction using inter-domain coevolution. PLoS Comput Biol 16(10): e1007621.

18. Gandarilla-Pérez, C.A., Mergny, P., Weigt, M. and Bitbol, A.F., 2020. Statistical physics of interacting proteins: impact of dataset size and quality assessed in synthetic sequences. Physical Review E, 101(3), p.032413.

19. Reimer, J.M., Eivaskhani, M., Harb, I., Guarné, A., Weigt, M. and Schmeing, T.M., 2019. Structures of a dimodular nonribosomal peptide synthetase reveal conformational flexibility. Science, 366(6466).

20. E. Rodriguez Horta, P. Barrat-Charlaix, M. Weigt "Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data". Entropy 21, 1090 (2019). https://doi.org/10.3390/e21111090

21. G. Croce, T. Gueudré, MV Ruiz Cuevas, V. Keidel, M. Figliuzzi, H. Szurmant, M. Weigt "A multi-scale coevolutionary approach to predict interactions between protein domains". PLoS Comput Biol 15(10): e1006891 (2019). https://doi.org/10.1371/journal.pcbi.1006891

22. G. Marmier, M. Weigt, A.-F. Bitbol, "Phylogenetic correlations can suffice to infer protein partners from sequences". PLoS Comput Biol 15(10): e1007179 (2019). https://doi.org/10.1371/journal.pcbi.1007179

23. K. Shimagaki, M. Weigt, "Selection of sequence motifs and generative Hopfield-Potts models for protein families", Phys. Rev. E 100, 032128 (2019)

24. N. Agier, S. Delmas, Q. Zhang, A. Fleiss, Y. Jaszczyszyn, E. van Dijk, C. Thermes, M. Weigt, M. Cosentino-Lagomarsino, G. Fischer, "The evolution of the temporal program of genome replication", Nature Comm. 9, 2199 (2018)

25. M. Figliuzzi, P. Barrat-Charlaix, M. Weigt, "How pairwise coevolutionary models capture the collective residue variability in proteins", Mol. Biol. Evol. 35, 1018-1027 (2018) https://doi.org/10.1093/molbev/msy007

26. A. Couce, L.V. Caudwell, C. Feinauer, T. Hindré, J.P. Feugeas, M. Weigt, R.E. Lenski, D. Schneider, and O. Tenaillon, "Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria", Proc. Natl. Acad. Sci. 114, E9026-E9036 (2017); doi:10.1073/pnas.1705887114 

27. C. Feinauer, M. Weigt, "Context-Aware Prediction of Pathogenicity of Missense Mutations Involved in Human Disease", preprint (2017).

28. G. Uguzzoni, S. John Lovis, F. Oteri, A. Schug, H. Szurmant, M. Weigt, "Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis", Proc. Natl. Acad. Sci. 114, E2662-E2671 (2017).
    Recommended by Faculty of 1000. 

29. P. Barrat-Charlaix , M. Figliuzzi , M. Weigt, "Improving landscape inference by integrating heterogeneous data in the inverse Ising problem",  Sci. Rep. 6, 37812 (2016); doi: 10.1038/srep37812

30. A. Coucke, G. Uguzzoni, F. Oteri, S. Cocco, R. Monasson and M. Weigt, "Direct coevolutionary couplings reflect biophysical residue interactions in proteins", J. Chem. Phys. 145, 174102 (2016).

31. T. Gueudré, C. Baldassi , M. Zamparo , M. Weigt* , A. Pagnani*, "Simultaneous identification of specifically interacting paralogs and inter-protein contacts by Direct-Coupling Analysis", Proc. Natl. Acad. Sci.  113, 12186-12191 (2016). (* corr. author)
    Recommend by Faculty of 1000.

32. C. Feinauer, H. Szurmant, M. Weigt, A. Pagnani "Inter-Protein Sequence Co-Evolution Predicts Known Physical Interactions in Bacterial Ribosomes and the Trp Operon" PLoS ONE 11(2): e0149166 (2016). doi:10.1371/journal.pone.0149166
    Recommend by Faculty of 1000.

33. 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", Mol Biol Evol (2016) 33 (1): 268-280. doi: 10.1093/molbev/msv211
    Recommend by Faculty of 1000.

34. E. De Leonardis, B. Lutz, S. Ratz, S. Cocco, R. Monasson, A. Schug, M. Weigt "Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction",  Nucl. Acids Res. (2015) 43 (21): 10444-10455. doi: 10.1093/nar/gkv932
    Recommend by Faculty of 1000.

35. C. Baldassi, M. Zamparo, C. Feinauer, A. Procaccini, R. Zecchina, M. Weigt and A. Pagnani "Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners". PLoS ONE 9(3): e92721 (2014).

36. E.J. Molinelli, A. Korkut, W. Wang, M.L. Miller, N.P. Gauthier, X. Jing, P. Kaushik, G. He, G. Mills. D.B. Solit, C.A. Pratilas, M. Weigt, A. Braunstein, A. Pagnani, R. Zecchina, C. Sander, "Perturbation Biology: Inferring Signaling Networks in Cellular Systems", PLOS Comp. Biol. 9(12), e1003290 (2013).

37. S. Cocco, R. Monasson, M. Weigt, "Inference of Hopfield-Potts patterns from covariation in protein families: calculation and statistical error bars", J. Phys.: Conf. Series 473, 012010 (2013).

38. S. Cocco, R. Monasson, M. Weigt, "From principal component to direct coupling analysis of coevolution in proteins: Low-eigenvalue modes are needed for structure prediction", PLoS Comp. Biol. 9(8): e1003176 (2013).

39. M Ekeberg, C. Lövkvist, Y. Lan, M. Weigt, E. Aurell, "Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models", Phys. Rev. E 87, 012707 (2013).
    Recommend by Faculty of 1000.

40. J.I. Sułkowska, F. Morcos, M. Weigt, T. Hwa, J.N. Onuchic, "Genomics-Aided Structure Prediction", Proc. Natl. Acad. Sci. 109, 10340-10345 (2012).

41. A.E. Dago, A. Schug, A. Procaccini, J.A. Hoch, M. Weigt*, H. Szurmant*, "The Structural Basis of Histidine Kinase Autophosphorylation: Integrating Genomics, Molecular Dynamics and Mutagenesis", Proc. Natl. Acad. Sci. 109, E1733-E1742 (2012). (* corr. author)
    Recommend by Faculty of 1000.

42. F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks, C. Sander, R. Zecchina, J.N. Onuchic, T. Hwa, M. Weigt, "Direct-coupling analysis of residue co-evolution captures native contacts across many protein families", Proc. Natl. Acad. Sci. 108, E1293-E1301 (2011).
    Recommend by Faculty of 1000.

43. A. Procaccini, B. Lunt, H. Szurmant, T. Hwa, M. Weigt, "Dissecting the Specificity of Protein-Protein Interaction in Bacterial Two-Component Signaling: Orphans and Crosstalks", PLoS ONE 6(5): e19729 (2011).

44. M. Bailly-Bechet, A. Braunstein, A. Pagnani,  M. Weigt, R. Zecchina, "Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach", BMC Bioinformatics 11, 355 (2010).

45. S. Bradde, A. Braunstein, H. Mahmoudi, F. Tria, M. Weigt, R. Zecchina "Aligning graphs and finding substructures by message passing", Europhys. Lett. 89, 37009 (2010).

46. A. Schug, M. Weigt, J.A. Hoch, J.N. Onuchic, T. Hwa, H. Szurmant, "Computational modeling of phosphotransfer complexes in two-component signaling", Methods Enzymol 471 43-58 (2010).

47. B. Lunt, H. Szurmant, A. Procaccini, J.A. Hoch, T. Hwa, M. Weigt, "Inference of direct residue contacts in two-component signaling", Methods Enzymol 471 17-41 (2010).

48. A. Schug, M. Weigt, J.N. Onuchic, T. Hwa, H. Szurmant, "High resolution protein complexes from integrating genomic information with molecular simulation", Proc. Natl. Acad. Sci. 106, 22124 (2009).

49. A. Lage-Castellanos, A. Pagnani, M. Weigt, "Statistical mechanics of sparse generalization and model selection", J. Stat. Mech. P10009 (2009).

50. F. Tria, A. Pagnani, M. Weigt, "Classification and sparse-signature extraction from gene-expression data", J. Stat. Mech. P05001 (2009).

51. M. Weigt, R.A. White, H. Szurmant, J.A. Hoch, T. Hwa, "Identification of direct residue contacts in protein-protein interaction by message passing", Proc. Natl. Acad. Sci. 106, 67 (2009).
    Recommend by Faculty of 1000.

52. A. Braunstein, A. Pagnani, M. Weigt, R. Zecchina, "Inference algorithms for gene networks: A statistical-mechanics analysis", J. Stat. Mech. P12001 (2008).

53. Sumedha, M. Weigt, "A thermodynamic model for agglomeration of DNA looping proteins", J. Stat. Mech. P11005 (2008).

54. M. Leone, Sumedha, M. Weigt, "Unsupervised and semi-supervised clustering by message passing: Soft-constraint affinity propagation", Europ. Phys. J. B 66, 125 (2008).

55. A. Braunstein, A. Pagnani, M. Weigt, R. Zecchina, "Gene-network inference by message passing", J. Phys.: Conf. Series 95, 012016 (2008).

56. M. Leone, Sumedha, M. Weigt, "Clustering by soft-constraint affinity propagation: Applications to gene-expression data", Bioinformatics 23, 2708 (2007). Supplementary material: pdf.

57. H. Mahmoudi, A. Pagnani, M. Weigt, R. Zecchina, "Propagation of external regulation and asynchronous dynamics in random Boolean networks", Chaos 17, 026109 (2007).

58. R. Kühn, J. van Mourik, M. Weigt, A. Zippelius, "Finitely coordinated models for low-temperature phases of amorphous systems", J. Phys. A: Math. Theor. 40, 9227 (2007).

59. T. Galla, M. Leone, M. Marsili, M. Sellitto, M. Weigt, R. Zecchina, "Statistical mechanics of combinatorial auctions", Phys. Rev. Lett. 97, 128701 (2006).

60. M. Weigt, H. Zhou "Message passing for vertex covers" , Phys. Rev. E 74, 046110 (2006).

61. M. Pretti, M. Weigt, "Sudden emergence of q-regular subgraphs in random graphs" , Europhys. Lett. 75, 8 (2006).

62. M. Leone, M. Sellitto, M. Weigt, "Combinatorial auctions: From a statistical-physics approach to efficient algorithms" , Proceedings of the 2nd European Conference on Complex Systems (ECCS'05).

63. L. Correale, M. Leone, A. Pagnani, M. Weigt, R. Zecchina, "Computational core and fixed-point organization in Boolean networks" , J. Stat. Mech. P03002 (2006).

64. L. Correale, M. Leone, A. Pagnani, M. Weigt, R. Zecchina, "Core percolation and onset of complexity in Boolean networks" , Phys. Rev. Lett. 96, 018101 (2006).

65. X. Mao, P.M. Goldbart, M. Mezard, M. Weigt, "Cavity approach to the random solid state" , Phys. Rev. Lett. 95, 148302 (2005).

66. H. Hansen-Goos, M. Weigt, "A hard-sphere model on generalized Bethe lattices: Dynamics" , J. Stat. Mech. P08001 (2005).

67. H. Hansen-Goos, M. Weigt, "A hard-sphere model on generalized Bethe lattices: Statics" , J. Stat. Mech. P04006 (2005).

68. W. Barthel, A.K. Hartmann, M. Weigt, "Phase transition and finite-size scaling in the vertex-cover problem" , Comp. Phys. Comm. 169, 234 (2005)

69. F. Krzakala, A. Pagnani, M. Weigt, "Threshold values, stability analysis and high-q asymptotics for the coloring problem on random graphs" , Phys. Rev. E 70, 046705 (2004)

70. G. Semerjian and M. Weigt, "Approximation schemes for the dynamics of diluted spin models: the Ising ferromagnet on a Bethe lattice", J. Phys. A 37, 5525 (2004)

71. A. Braunstein, R. Mulet, A. Pagnani, M. Weigt, and R. Zecchina, "Polynomial iterative algorithms for coloring and analyzing random graphs", Phys. Rev. E 68, 036702 (2003)

72. W. Barthel, A. K. Hartmann, and M. Weigt, "Solving satisfiability problems by fluctuations: The dynamics of stochastic local search algorithms", Phys. Rev. E 67, 066104 (2003)

73. M. Weigt and A. K. Hartmann, "Glassy behavior induced by geometrical frustration in a hard-core lattice gas model", Europhys. Lett. 62, 533 (2003)

74. A. Vazquez and M. Weigt, "Computational complexity arising from degree correlations in networks" , Phys. Rev. E 67, 027101 (2003)

75. R. Mulet, A. Pagnani, M. Weigt, and R. Zecchina, "Coloring random graphs" , Phys. Rev. Lett. 89, 268701 (2002)

76. K. Broderix, M. Weigt, and A. Zippelius, "Towards finite-dimensional gelation", Eur. Phys. J. B 29, 441 (2002)

77. M. Weigt, "Dynamics of heuristic optimization algorithms on random graphs", Eur. Phys. J. B 28, 369 (2002)

78. W. Barthel, A. K. Hartmann, M. Leone, F. Ricci-Tersenghi, M. Weigt, and R. Zecchina, "Hiding solutions in random satisfiability problems: A statistical mechanics approach", Phys. Rev. Lett. 88, 188701 (2002)

79. S. Franz, M. Mezard, F. Ricci-Tersenghi, M. Weigt, and R. Zecchina, "A ferromagnet with a glass transition", Europhys. Lett. 55, 465 (2001)

80. M. Weigt and A. K. Hartmann, "Minimal vertex covers on finite-connectivity random graphs - a hard-sphere lattice-gas picture", Phys. Rev. E 63, 056127 (2001)

81. M. Weigt and A. K. Hartmann, "Typical solution time for a vertex-covering algorithm on finite-connectivity random graphs", Phys. Rev. Lett. 86, 1658 (2001)

82. F. Ricci-Tersenghi, M. Weigt, and R. Zecchina, "Simplest random K-satisfiability problem", Phys. Rev. E 63, 026702 (2001)

83. A. K. Hartmann and M. Weigt, "Statistical mechanics perspective on the phase transition in vertex covering of finite-connectivity random graphs", Theor. Comp. Sci. 265, 199 (2001)

84. M. Weigt and A. K. Hartmann, "The number of guards needed by a museum: A phase transition in vertex covering of random graphs", Phys. Rev. Lett. 84, 6118 (2000)
    reported by P. Ball in nature science update

85. G. Biroli, R. Monasson, and M. Weigt, "A variational description of the ground state structure in random satisfiability problems", Europ. Phys. J. B 14, 551 (2000)

86. A. Barrat and M. Weigt, "On the properties of small-world network models", Europ. Phys. J. B 13, 547 (2000)

87. reprinted in M. Newman, A.L. Barabasi, D. Watts "The Structure and Dynamics of Networks" (Princeton University Press, Princeton 2006).

88. J. Berg and M. Weigt, "Entropy and typical properties of Nash equilibria in two-player games", Europhys. Lett. 48, 129 (1999)

89. M. Weigt, "A replica approach to products of random matrices", J. Phys. A: Math. Gen. 31, 951 (1998)

90. M. Weigt, "Multifractal analysis of perceptron learning with errors", Phys. Rev. E 57, 955 (1998)

91. M. Weigt and A. Engel, "Multifractality and percolation in the coupling space of perceptrons", Phys. Rev. E 55, 4552 (1997)

92. M. Weigt and R. Monasson, "Replica structure of one-dimensional disordered Ising models", Europhys. Lett. 36, 209 (1996)

93. A. Engel and M. Weigt, "Multifractal analysis of the coupling space of feedforward neural networks", Phys. Rev. E 53, R2064 (1996)

94. R. Dick and M. Weigt, "Cohomology of Lie algebra and operator product expansions in two dimensions" in Group Theoretical Methods in Physics, Vol. 2, Editors: M.A. del Olmo, M. Santander and J. Mateos Guilarte, CIEMAT, Madrid 1993, pp. 86-90

95. A. Engel and M. Weigt, "Storage capacity of the truncated projection rule" , J. Phys. A: Math. Gen. 24, 3707 (1991)

Book contributions and small reviews:

1. Cocco, S., De Martino, A., Pagnani, A., & Weigt, M. (2022). Statistical-physics approaches to RNA molecules, families and networks. arXiv preprint arXiv:2207.13402, to appear in "Spin Glass Theory and Far Beyond - Replica Symmetry Breaking after 40 years" (edited by P Charbonneau, E Marinari, G Parisi, F Ricci Tersenghi, G Sicuro and F Zamponi)

2. T. Gueudré, C. Baldassi, A. Pagnani, M. Weigt  "Predicting Interacting Protein Pairs by Coevolutionary Paralog Matching". In: Canzar S., Ringeling F. (eds) Protein-Protein Interaction Networks. Methods in Molecular Biology, vol 2074. Humana, New York, NY (2020).

3. P. Barrat-Charlaix, M. Weigt, "De la variabilité des séquences à la prédiction structurale et fonctionnelle : modélisation de familles de protéines homologues", Biologie Aujourd’hui 211 (3), 239-244 (2017)

4. F. Morcos, T. Hwa, JN. Onuchic, M. Weigt, "Direct Coupling Analysis for Contact Prediction", in Protein Structure Prediction, ed. D. Kihara, Methods in Molecular Biology, Volume 1137, 55 (2014)

5. M. Weigt and H. Szurmant, "Genetic Covariation", in Brunner's Encyclopedia of Genetics (Academic Press 2013)

6. A. Lage-Castellanos, A. Pagnani, M. Weigt, "The importance of dilution in the inference of biological networks", in Communication, Control, and Computing, 2009. Allerton 2009. 531-538.

7. A.K. Hartmann and M. Weigt, "Statistical mechanics of the vertex-cover problem", review article, J. Phys. A: Math. Gen. 36, 11069 (2003)

8. M. Weigt, "The random 3-satisfiability problem: From the phase transition to the efficient generation of hard, but satisfiable problem instances", in New Optimization Algorithms in Physics, Editors: A.K. Hartmann and H. Rieger (Wiley-VCH, Weinheim 2004)

9. A. Braunstein, M. Mezard, M. Weigt, and R. Zecchina, "Constraint Satisfaction by Survey Propagation", in Computational Complexity and Statistical Physics, Editors: A. Percus, G. Istrate and C. Moore (2005)

Theses:

1. M. Weigt, "Statistical physics of combinatorial optimization problems, and related physical models", Habilitation thesis (2005)

2. M. Weigt, "Replikatheorie ungeordneter Systeme: Neuronale Netze und niedrigdimensionale Modelle", PhD thesis (1998)

3. M. Weigt, "Konforme Operatoralgebren auf zweifach und dreifach punktierten Sphären", Diploma Thesis (1993)