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Meynard-Piganeau B, Feinauer C, Weigt M, Walczak AM, Mora T. TULIP: A transformer-based unsupervised language model for interacting peptides and T cell receptors that generalizes to unseen epitopes. Proceedings of the National Academy of Sciences. 121, pp.e2316401121 (2024).
Calvanese F, Lambert CN, Nghe P, Zamponi F, Weigt M. Towards parsimonious generative modeling of RNA families. Nucleic Acids Research. pp.gkae289 (2024).
Meynard-Piganeau B, Fabbri C, Weigt M, Pagnani A, Feinauer C. Generating interacting protein sequences using domain-to-domain translation. Bioinformatics. 39, pp.btad401 (2023).
Gandarilla-Pérez CA, Pinilla S, Bitbol A-F, Weigt M. Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins. PLoS Comp Biol. 19(3), pp.e1011010 (2023).
Ciarella S, Trinquier J, Weigt M, Zamponi F. Machine-learning-assisted Monte Carlo fails at sampling computationally hard problems. Machine Learning: Science and Technology. 4, pp.010501 (2023).
Patteson JB, Fortinez CMarie, Putz AT, Rodriguez-Rivas J, L. Bryant H, Adhikari K, Weigt M, T. Schmeing M, Li B. Structure and Function of a Dehydrating Condensation Domain in Nonribosomal Peptide Biosynthesis. Journal of the American Chemical Society. 144(31), pp.14057 - 14070 (2022).
Vigué L, Croce G, Petitjean M, Ruppé E, Tenaillon O, Weigt M. Deciphering polymorphism in 61,157 Escherichia coli genomes via epistatic sequence landscapes. Nature Communications. 13(1), pp.4030 (2022).
Rodriguez-Rivas J, Croce G, Muscat M, Weigt M. Epistatic models predict mutable sites in SARS-CoV-2 proteins and epitopes. Proceedings of the National Academy of Sciences. 119, pp. e2113118119 (2022).
Trinquier J, Uguzzoni G, Pagnani A, Zamponi F, Weigt M. Efficient generative modeling of protein sequences using simple autoregressive models. Nature Communications. 12(1), pp.5800 (2021).
Muntoni AP, Pagnani A, Weigt M, Zamponi F. adabmDCA: adaptive Boltzmann machine learning for biological sequences. BMC Bioinformatics. 22(1), pp.528 (2021).
Bisardi M, Rodriguez-Rivas J, Zamponi F, Weigt M. Modeling Sequence-Space Exploration and Emergence of Epistatic Signals in Protein Evolution. Molecular Biology and Evolution. (2021).
Rodriguez-Horta E, Lage A, Weigt M, Barrat-Charlaix P. Global multivariate model learning from hierarchically correlated data. J. Stat. Mech. (2021).
Barrat-Charlaix P, Muntoni AP, Shimagaki K, Weigt M, Zamponi F. Sparse generative modeling via parameter reduction of Boltzmann machines: Application to protein-sequence families. Phys. Rev. E. 104, pp.024407 (2021).
Rodriguez-Horta E, Weigt M. On the effect of phylogenetic correlations in coevolution-based contact prediction in proteins. PLOS Computational Biology. 17, pp.1-17 (2021).
Danko D, Bezdan D, Afshin EE, Ahsanuddin S, Bhattacharya C, Butler DJ, Chng KRei, Donnellan D, Hecht J, Jackson K, Kuchin K, Karasikov M, Lyons A, Mak L, Meleshko D, Mustafa H, Mutai B, Neches RY, Ng A, Nikolayeva O, Nikolayeva T, Png E, Ryon KA, Sanchez JL, Shaaban H, Sierra MA, Thomas D, Young B, Abudayyeh OO, Alicea J, Bhattacharyya M, Blekhman R, Castro-Nallar E, Cañas AM, Chatziefthimiou AD, Crawford RW, De Filippis F, Deng Y, Desnues C, Dias-Neto E, Dybwad M, Elhaik E, Ercolini D, Frolova A, Gankin D, Gootenberg JS, Graf AB, Green DC, Hajirasouliha I, Hastings JJA, Hernandez M, Iraola G, Jang S, Kahles A, Kelly FJ, Knights K, Kyrpides NC, Łabaj PP, Lee PKH, Leung MHY, Ljungdahl PO, Mason-Buck G, McGrath K, Meydan C, Mongodin EF, Moraes MOzorio, Nagarajan N, Nieto-Caballero M, Noushmehr H, Oliveira M, Ossowski S, Osuolale OO, Özcan O, Paez-Espino D, Rascovan N, Richard H, Rätsch G, Schriml LM, Semmler T, Sezerman OU, et al.. A global metagenomic map of urban microbiomes and antimicrobial resistance. Cell . (2021).


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