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Pierre Barrat-Charlaix
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Global multivariate model learning from hierarchically correlated data. J. Stat. Mech. (2021).
. Sparse generative modeling via parameter reduction of Boltzmann machines: Application to protein-sequence families. Phys. Rev. E. 104, pp.024407 (2021).
. An evolution-based model for designing chorismate mutase enzymes. Science. 369, pp.440–445 (2020).
. Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data. Entropy. 21, pp.1090 (2019).
. How Pairwise Coevolutionary Models Capture the Collective Residue Variability in Proteins?. Molecular Biology and Evolution. pp.msy007 (2018).
. De la variabilité des séquences à la prédiction structurale et fonctionnelle : modélisation de familles de protéines homologues. Biologie Aujourd’hui. 211(3), pp.239-244 (2017).
. Improving landscape inference by integrating heterogeneous data in the inverse Ising problem. Sci. Rep. 6, 37812, (2016).
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