| TorchMD: A deep learning framework for molecular simulations S Doerr, M Majewski, A Pérez, A Kramer, C Clementi, F Noe, T Giorgino, ... Journal of chemical theory and computation 17 (4), 2355-2363, 2021 | 161 | 2021 |
| Coarse graining molecular dynamics with graph neural networks BE Husic, NE Charron, D Lemm, J Wang, A Pérez, M Majewski, A Krämer, ... The Journal of chemical physics 153 (19), 2020 | 153 | 2020 |
| Cap analogs modified with 1, 2-dithiodiphosphate moiety protect mRNA from decapping and enhance its translational potential M Strenkowska, R Grzela, M Majewski, K Wnek, J Kowalska, ... Nucleic acids research 44 (20), 9578-9590, 2016 | 79 | 2016 |
| An investigation of structural stability in protein-ligand complexes reveals the balance between order and disorder M Majewski, S Ruiz-Carmona, X Barril Communications Chemistry 2 (1), 110, 2019 | 56 | 2019 |
| Structure based virtual screening: Fast and slow A Varela‐Rial, M Majewski, G De Fabritiis Wiley Interdisciplinary Reviews: Computational Molecular Science 12 (2), e1544, 2022 | 36 | 2022 |
| Machine learning coarse-grained potentials of protein thermodynamics M Majewski, A Pérez, P Thölke, S Doerr, NE Charron, T Giorgino, ... Nature communications 14 (1), 5739, 2023 | 34 | 2023 |
| Structural stability predicts the binding mode of protein–ligand complexes M Majewski, X Barril Journal of Chemical Information and Modeling 60 (3), 1644-1651, 2020 | 14 | 2020 |
| PlayMolecule glimpse: understanding protein–ligand property predictions with interpretable neural networks A Varela-Rial, I Maryanow, M Majewski, S Doerr, N Schapin, ... Journal of chemical information and modeling 62 (2), 225-231, 2022 | 13 | 2022 |
| SkeleDock: a web application for scaffold docking in PlayMolecule A Varela-Rial, M Majewski, A Cuzzolin, G Martínez-Rosell, G De Fabritiis Journal of chemical information and modeling 60 (6), 2673-2677, 2020 | 9 | 2020 |
| Fragment-to-lead tailored in silico design M Rachman, S Piticchio, M Majewski, X Barril Drug Discovery Today: Technologies 40, 44-57, 2021 | 8 | 2021 |
| Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series F Sabanés Zariquiey, A Pérez, M Majewski, E Gallicchio, G De Fabritiis Journal of chemical information and modeling 63 (8), 2438-2444, 2023 | 7 | 2023 |
| Dynamic undocking: a novel method for structure-based drug discovery M Majewski, S Ruiz-Carmona, X Barril Rational Drug Design: Methods and Protocols, 195-215, 2018 | 6 | 2018 |
| Nucleotide-decorated AuNPs as probes for nucleotide-binding proteins O Perzanowska, M Majewski, M Strenkowska, P Głowala, ... Scientific Reports 11 (1), 15741, 2021 | 5 | 2021 |
| Navigating protein landscapes with a machine-learned transferable coarse-grained model NE Charron, F Musil, A Guljas, Y Chen, K Bonneau, AS Pasos-Trejo, ... arXiv preprint arXiv:2310.18278, 2023 | 4 | 2023 |
| Machine learning small molecule properties in drug discovery N Schapin, M Majewski, A Varela-Rial, C Arroniz, G De Fabritiis Artificial Intelligence Chemistry, 100020, 2023 | 4 | 2023 |
| Top-down machine learning of coarse-grained protein force fields C Navarro, M Majewski, G De Fabritiis Journal of Chemical Theory and Computation 19 (21), 7518-7526, 2023 | 3 | 2023 |
| AceGen: A TorchRL-based toolkit for reinforcement learning in generative chemistry A Bou, M Thomas, S Dittert, CN Ramírez, M Majewski, Y Wang, S Patel, ... ICLR 2024 Workshop on Generative and Experimental Perspectives for …, 0 | 2* | |
| Implications of Structural Stability for Drug Design M Majewski Universitat de Barcelona, 2020 | | 2020 |
| Supplementary Information SkeleDock: A Web Application for Scaffold Docking in PlayMolecule A Varela-Rial, M Majewski, A Cuzzolin, G Martınez-Rosell, G De Fabritiis | | |
Gianni De FabritiisComputational Science Laboratory, Icrea Research Professor, Acellera twitter:@gdefabritiis在 upf.edu 的电子邮件经过验证
