Pierre Barrat-Charlaix
Pierre Barrat-Charlaix
Verified email at unibas.ch
Title
Cited by
Cited by
Year
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
372018
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
302020
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
122016
Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data
E Rodriguez Horta, P Barrat-Charlaix, M Weigt
Entropy 21 (11), 1090, 2019
52019
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
42020
Limited predictability of amino acid substitutions in seasonal influenza viruses
P Barrat-Charlaix, J Huddleston, T Bedford, R Neher
BioRxiv, 2020
32020
Evolution-based design of chorismate mutase enzymes
WP Russ, M Figliuzzi, C Stocker, P Barrat-Charlaix, M Socolich, P Kast, ...
bioRxiv, 2020
22020
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
Sparse generative modeling of protein-sequence families
P Barrat-Charlaix, AP Muntoni, K Shimagaki, M Weigt, F Zamponi
arXiv preprint arXiv:2011.11259, 2020
12020
Global multivariate model learning from hierarchically correlated data
ER Horta, A Lage, M Weigt, P Barrat-Charlaix
arXiv preprint arXiv:2102.06036, 2021
2021
Global multivariate model learning from hierarchically correlated data
E Rodriguez Horta, A Lage, M Weigt, P Barrat-Charlaix
arXiv e-prints, arXiv: 2102.06036, 2021
2021
Comprendre et améliorer les modèles statistiques de séquences de protéines
P Barrat-Charlaix
Sorbonne université, 2018
2018
Understanding and improving statistical models of protein sequences
P Barrat-Charlaix
Sorbonne Université, 2018
2018
From sequence variability to structural and functional prediction: modeling of homologous protein families
P Barrat-Charlaix, M Weigt
Biologie aujourd'hui 211 (3), 239-244, 2017
2017
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
Supplementary Material S1: Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data
ER Horta, P Barrat-Charlaix, M Weigt
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