| Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning F Noé*, S Olsson*, J Köhler*, H Wu Science 365 (6457), eaaw1147, 2019 | 775 | 2019 |
| Machine learning of coarse-grained molecular dynamics force fields J Wang, S Olsson, C Wehmeyer, A Perez, N Charron, G De Fabritiis, ... ACS Cent. Sci. 5 (5), 755-767, 2019 | 499 | 2019 |
| Camostat mesylate inhibits SARS-CoV-2 activation by TMPRSS2-related proteases and its metabolite GBPA exerts antiviral activity M Hoffmann, H Hofmann-Winkler, JC Smith, N Krüger, P Arora, ... EBioMedicine 65, 2021 | 355 | 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 | 181 | 2020 |
| Combining experimental and simulation data of molecular processes via augmented Markov models S Olsson, H Wu, F Paul, C Clementi, F Noé Proceedings of the National Academy of Sciences 114 (31), 8265-8270, 2017 | 113 | 2017 |
| Molecular mechanism of inhibiting the SARS-CoV-2 cell entry facilitator TMPRSS2 with camostat and nafamostat T Hempel, L Raich, S Olsson, NP Azouz, AM Klingler, M Hoffmann, ... Chemical Science 12 (3), 983-992, 2021 | 102* | 2021 |
| De Novo Drug Design Using Reinforcement Learning with Graph-Based Deep Generative Models SR Atance, JV Diez, O Engkvist, S Olsson, R Mercado Journal of chemical information and modeling 62 (20), 4863-4872, 2022 | 91 | 2022 |
| Bayesian inference of protein ensembles from SAXS data LD Antonov, S Olsson, W Boomsma, T Hamelryck Physical Chemistry Chemical Physics 18 (8), 5832-5838, 2016 | 65 | 2016 |
| Inference of structure ensembles of flexible biomolecules from sparse, averaged data S Olsson, J Frellsen, W Boomsma, KV Mardia, T Hamelryck PloS one 8 (11), e79439, 2013 | 62 | 2013 |
| Multi-body effects in a coarse-grained protein force field J Wang, N Charron, B Husic, S Olsson, F Noé, C Clementi The Journal of Chemical Physics 154 (16), 2021 | 53 | 2021 |
| PHAISTOS: a framework for Markov chain Monte Carlo simulation and inference of protein structure W Boomsma, J Frellsen, T Harder, S Bottaro, KE Johansson, P Tian, ... Journal of computational chemistry 34 (19), 1697-1705, 2013 | 48 | 2013 |
| Mechanistic models of chemical exchange induced relaxation in protein NMR S Olsson, F Noé Journal of the American Chemical Society 139 (1), 200-210, 2017 | 46 | 2017 |
| The exact NOE as an alternative in ensemble structure determination B Vögeli, S Olsson, P Güntert, R Riek Biophysical journal 110 (1), 113-126, 2016 | 45 | 2016 |
| Probabilistic Determination of Native State Ensembles of Proteins. S Olsson, BR Vögeli, A Cavalli, W Boomsma, J Ferkinghoff-Borg, ... Journal of Chemical Theory and Computation, 2014 | 43 | 2014 |
| Dynamic graphical models of molecular kinetics S Olsson, F Noé Proceedings of the National Academy of Sciences 116 (30), 15001-15006, 2019 | 40 | 2019 |
| Camostat mesylate inhibits SARS-CoV-2 activation by TMPRSS2-related proteases and its metabolite GBPA exerts antiviral activity. EBioMedicine. 2021; 65: 103255 M Hoffmann, H Hofmann-Winkler, JC Smith, N Krüger, P Arora, ... DOI 10 (2020.08), 05.237651, 2021 | 39 | 2021 |
| Discovery of a hidden transient state in all bromodomain families L Raich, K Meier, J Günther, CD Christ, F Noé, S Olsson Proceedings of the National Academy of Sciences 118 (4), e2017427118, 2021 | 32 | 2021 |
| Implicit transfer operator learning: Multiple time-resolution models for molecular dynamics M Schreiner, O Winther, S Olsson Advances in Neural Information Processing Systems 36, 36449-36462, 2023 | 29 | 2023 |
| Protein allostery at atomic resolution D Strotz, J Orts, H Kadavath, M Friedmann, D Ghosh, S Olsson, CN Chi, ... Angewandte Chemie International Edition 59 (49), 22132-22139, 2020 | 29 | 2020 |
| The exact nuclear overhauser enhancement: recent advances PJ Nichols, A Born, MA Henen, D Strotz, J Orts, S Olsson, P Güntert, ... Molecules 22 (7), 1176, 2017 | 29 | 2017 |
Noe FrankMicrosoft ResearchVerified email at microsoft.com
