Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning P Gainza, F Sverrisson, F Monti, E Rodola, D Boscaini, MM Bronstein, ... Nature Methods 17 (2), 184-192, 2020 | 583 | 2020 |
Fast end-to-end learning on protein surfaces F Sverrisson, J Feydy, BE Correia, MM Bronstein Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 129 | 2021 |
De novo design of protein interactions with learned surface fingerprints P Gainza, S Wehrle, A Van Hall-Beauvais, A Marchand, A Scheck, ... Nature 617 (7959), 176-184, 2023 | 86 | 2023 |
Rosetta FunFolDes–A general framework for the computational design of functional proteins J Bonet, S Wehrle, K Schriever, C Yang, A Billet, F Sesterhenn, A Scheck, ... PLoS computational biology 14 (11), e1006623, 2018 | 39 | 2018 |
Physics-informed deep neural network for rigid-body protein docking F Sverrisson, J Feydy, J Southern, MM Bronstein, BE Correia MLDD 2022-Machine Learning for Drug Discovery Workshop of ICLR 2022, 2022 | 16 | 2022 |
Fast end-to-end learning on protein surfaces. 2021 IEEE F Sverrisson, J Feydy, BE Correia, MM Bronstein CVF Conference on Computer Vision and Pattern Recognition (CVPR) 15267, 15276, 2021 | 12 | 2021 |
Deciphering interaction fingerprints from protein molecular surfaces P Gainza, F Sverrisson, F Monti, E Rodola, MM Bronstein, BE Correia BioRxiv, 606202, 2019 | 10 | 2019 |
Rodola, E., Boscaini, D., Bronstein, MM, and Correia, BE (2020). Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning P Gainza, F Sverrisson, F Monti Nat. Methods 17, 184-192, 0 | 9 | |
De novo design of site-specific protein interactions with learned surface fingerprints P Gainza, S Wehrle, A Van Hall-Beauvais, A Marchand, A Scheck, ... bioRxiv, 2022.06. 16.496402, 2022 | 6 | 2022 |
Decoding surface fingerprints for protein-ligand interactions I Igashov, AR Jamasb, A Sadek, F Sverrisson, A Schneuing, P Lio, ... bioRxiv, 2022.04. 26.489341, 2022 | 4 | 2022 |
DiffMaSIF: Surface-based Protein-Protein Docking with Diffusion Models F Sverrisson, M Akdel, D Abramson, J Feydy, A Goncearenco, Y Adeshina, ... Machine Learning in Structural Biology workshop at NeurIPS 2023, 2023 | 1 | 2023 |
Predicting protein interactions using geometric deep learning on protein surfaces F Sverrisson EPFL, 2024 | | 2024 |
Systems and methods for de novo design of protein interactions with learned surface fingerprints PG Cirauqui, S Wehrle, A Van Hall-Beauvais, A Marchand, A Scheck, ... US Patent App. 18/206,873, 2023 | | 2023 |
A method and system for fast end-to-end learning on protein surfaces M Bronstein, F Sverrisson, J Pierre Feydy, P Gainza, ... | | 2022 |
De Novo Design of Site-specific Protein Binders Using Surface Fingerprints S Wehrle, V Hall-Beauvais, P Gainza, Z Harteveld, A Scheck, F Sverrisson, ... Protein Science 30, 162-163, 2021 | | 2021 |
Decrypting interaction fingerprints in protein molecular surfaces P Gainza, F Sverrisson, F Monti, M Bronstein, B Correia European Biophysics Journal With Biophysics Letters 48, S224-S224, 2019 | | 2019 |
Learning interaction patterns from surface representations of protein structure. P Gainza, F Sverrisson, F Monti, E Rodolà, D Boscaini, M Bronstein, ... Proceedings of Workshop on Graph Representation Learning at the 33rd …, 2019 | | 2019 |
DiffMaSIF: Score-Based Diffusion Models for Protein Surfaces F Sverrisson, M Akdel, D Abramson, J Feydy, A Goncearenco, Y Adeshina, ... | | |
LPDI S Balharry, L Bonati, J Bonet Martinez, SM Buckley, KM Castro Gilabert, ... | | |
Mat á styrkgildum umbrotsefna í efnaskiptalíkönum með Monte Carlo hermun F Sverrisson | | |