| Seven amino acid types suffice to create the core fold of RNA polymerase S Yagi, AK Padhi, J Vucinic, S Barbe, T Schiex, R Nakagawa, D Simoncini, ... Journal of the American Chemical Society 143 (39), 15998-16006, 2021 | 32 | 2021 |
| Positive multistate protein design J Vucinic, D Simoncini, M Ruffini, S Barbe, T Schiex Bioinformatics 36 (1), 122-130, 2020 | 27 | 2020 |
| Guaranteed diversity and optimality in cost function network based computational protein design methods M Ruffini, J Vucinic, S de Givry, G Katsirelos, S Barbe, T Schiex Algorithms 14 (6), 168, 2021 | 19 | 2021 |
| A comparative study to decipher the structural and dynamics determinants underlying the activity and thermal stability of GH-11 xylanases J Vucinic, G Novikov, CY Montanier, C Dumon, T Schiex, S Barbe International Journal of Molecular Sciences 22 (11), 5961, 2021 | 15 | 2021 |
| Guaranteed diversity & quality for the weighted CSP M Ruffini, J Vucinic, S de Givry, G Katsirelos, S Barbe, T Schiex 2019 IEEE 31st international conference on tools with artificial …, 2019 | 15 | 2019 |
| Complete combinatorial mutational enumeration of a protein functional site enables sequence‐landscape mapping and identifies highly‐mutated variants that retain activity MS Colom, J Vučinić, J Adolf‐Bryfogle, JW Bowman, S Verel, ... Protein Science 33 (8), e5109, 2024 | 1 | 2024 |
| Deep evolutionary forecasting identifies highly-mutated SARS-CoV-2 variants via functional sequence-landscape enumeration MS Colom, J Vucinic, J Adolf-Bryfogle, JW Bowman, S Verel, ... | 1 | 2022 |
| Seven amino acid types suffice to reconstruct the core fold of RNA polymerase S Yagi, A Padhi, J Vucinic, S Barbe, T Schiex, R Nakagawa, D Simoncini, ... | | 2023 |
| Molecular Modeling and Artificial Intelligence for Computational Protein Design: conception of optimized enzymes and nanobodies J Vucinic INSA de Toulouse, 2021 | | 2021 |
| Modélisation moléculaire et Intelligence Artificielle pour le design computationnel de protéines: conception d'enzymes optimisées et de nano-anticorps J Vucinic, S Barbe, T Schiex | | 2021 |
| Computational strategy for protein design based on structure-dynamics-activity relationship insights: GH11Xylanases as a casestudy G Novikov, J Vucinic, C Montanier, T Schiex, C Dumon, S Barbe 13. Carbohydrate Bioengineering Meeting, 2019 | | 2019 |
| Pushing the computational frontiers of multistate protein design J Vucinic, M Ruffini, D Simoncini, T Schiex, S Barbe GGMM 2019, 2019 | | 2019 |
| Qualité et diversité garanties dans les réseaux de fonctions de coût M Ruffini, J Vucinic, S De Givry, G Katsirelos, S Barbe, T Schiex Proceedings of PROGRAMMATION PAR CONTRAINTES. JOURNEES FRANCOPHONES. 15TH …, 2019 | | 2019 |
| Constraint Programming and Graphical models-Pushing data into your models, The protein design case. T Schiex, S Barbe, D Simoncini, J Vucinic, M Ruffini, D Allouche 23rd International Symposium on Mathematical Programming (ISMP-18), np, 2018 | | 2018 |
| Guaranted Diversity and Optimality for Computational Protein Design. Preprints 2021, 1, 0 M Ruffini, J Vucinic, S de Givry, G Katsirelos, S Barbe, T Schiex Bioinformatics 40, 389-408, 2000 | | 2000 |