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Pierre Barrat-Charlaix
Pierre Barrat-Charlaix
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Title
Cited by
Cited by
Year
An evolution-based model for designing chorismate mutase enzymes
WP Russ, M Figliuzzi, C Stocker, P Barrat-Charlaix, M Socolich, P Kast, ...
Science 369 (6502), 440-445, 2020
1112020
How pairwise coevolutionary models capture the collective residue variability in proteins?
M Figliuzzi, P Barrat-Charlaix, M Weigt
Molecular Biology and Evolution 35 (4), 1018-1027, 2018
632018
Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data
E Rodriguez Horta, P Barrat-Charlaix, M Weigt
Entropy 21 (11), 1090, 2019
152019
Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution
J Huddleston, JR Barnes, T Rowe, X Xu, R Kondor, DE Wentworth, ...
eLife 9, e60067, 2020
142020
Improving landscape inference by integrating heterogeneous data in the inverse Ising problem
P Barrat-Charlaix, M Figliuzzi, M Weigt
Scientific reports 6 (1), 1-9, 2016
142016
Sparse generative modeling via parameter reduction of Boltzmann machines: Application to protein-sequence families
P Barrat-Charlaix, AP Muntoni, K Shimagaki, M Weigt, F Zamponi
Physical Review E 104 (2), 024407, 2021
10*2021
Limited predictability of amino acid substitutions in seasonal influenza viruses
P Barrat-Charlaix, J Huddleston, T Bedford, RA Neher
Molecular Biology and Evolution 38 (7), 2767-2777, 2021
62021
Global multivariate model learning from hierarchically correlated data
ER Horta, A Lage-Castellanos, M Weigt, P Barrat-Charlaix
Journal of Statistical Mechanics: Theory and Experiment 2021 (7), 073501, 2021
22021
Methods for adaptive optimization of enhanced oil recovery performance under uncertainty
N Chugunov, TS Ramakrishnan, P Barrat-Charlaix
US Patent App. 14/949,032, 2016
22016
Understanding and improving statistical models of protein sequences
P Barrat-Charlaix
Sorbonne Université, 2018
12018
TreeKnit: Inferring Ancestral Reassortment Graphs of influenza viruses
P Barrat-Charlaix, T Vaughan, R Neher
bioRxiv, 2021
2021
Comprendre et améliorer les modèles statistiques de séquences de protéines
P Barrat-Charlaix
Sorbonne université, 2018
2018
De la variabilité des séquences à la prédiction structurale et fonctionnelle: modélisation de familles de protéines homologues
P Barrat-Charlaix, M Weigt
Biologie Aujourd'hui 211 (3), 239-244, 2017
2017
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Articles 1–13