Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... Nature 596 (7873), 583-589, 2021 | 4550 | 2021 |
The kinetics human action video dataset W Kay, J Carreira, K Simonyan, B Zhang, C Hillier, S Vijayanarasimhan, ... arXiv preprint arXiv:1705.06950, 2017 | 2395 | 2017 |
Improved protein structure prediction using potentials from deep learning AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ... Nature 577 (7792), 706-710, 2020 | 1778 | 2020 |
Highly accurate protein structure prediction for the human proteome K Tunyasuvunakool, J Adler, Z Wu, T Green, M Zielinski, A Žídek, ... Nature 596 (7873), 590-596, 2021 | 690 | 2021 |
Human-level performance in 3D multiplayer games with population-based reinforcement learning M Jaderberg, WM Czarnecki, I Dunning, L Marris, G Lever, AG Castaneda, ... Science 364 (6443), 859-865, 2019 | 597 | 2019 |
Population based training of neural networks M Jaderberg, V Dalibard, S Osindero, WM Czarnecki, J Donahue, ... arXiv preprint arXiv:1711.09846, 2017 | 545 | 2017 |
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models M Varadi, S Anyango, M Deshpande, S Nair, C Natassia, G Yordanova, ... Nucleic acids research 50 (D1), D439-D444, 2022 | 452 | 2022 |
Protein complex prediction with AlphaFold-Multimer R Evans, M O'Neill, A Pritzel, N Antropova, AW Senior, T Green, A Žídek, ... BioRxiv, 2021 | 263 | 2021 |
Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13) AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ... Proteins: Structure, Function, and Bioinformatics 87 (12), 1141-1148, 2019 | 219 | 2019 |
De novo structure prediction with deeplearning based scoring R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, A Zidek, ... Annu Rev Biochem 77 (363-382), 6, 2018 | 124 | 2018 |
High accuracy protein structure prediction using deep learning J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ... Fourteenth Critical Assessment of Techniques for Protein Structure …, 2020 | 116 | 2020 |
Elucidation of the Al/Si ordering in Gehlenite Ca2Al2SiO7 by combined 29Si and 27Al NMR spectroscopy/quantum chemical calculations P Florian, E Véron, T Green, JR Yates, D Massiot Chemistry of Materials, 2012 | 95 | 2012 |
Computational predictions of protein structures associated with COVID-19 J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, A Team DeepMind website, 2020 | 66* | 2020 |
Applying and improving AlphaFold at CASP14 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... Proteins: Structure, Function, and Bioinformatics 89 (12), 1711-1721, 2021 | 64 | 2021 |
Visualization and processing of computed solid-state NMR parameters: MagresView and MagresPython S Sturniolo, TFG Green, RM Hanson, M Zilka, K Refson, P Hodgkinson, ... Solid state nuclear magnetic resonance 78, 64-70, 2016 | 54 | 2016 |
Relativistic nuclear magnetic resonance J-coupling with ultrasoft pseudopotentials and the zeroth-order regular approximation TFG Green, JR Yates J. Chem. Phys., 234106, 2014 | 40 | 2014 |
Unusual Intermolecular “Through-Space” J Couplings in P–Se Heterocycles P Sanz Camacho, KS Athukorala Arachchige, AMZ Slawin, TFG Green, ... Journal of the American Chemical Society 137 (19), 6172-6175, 2015 | 19 | 2015 |
Investigating unusual homonuclear intermolecular “through-space” J couplings in organochalcogen systems P Sanz Camacho, D McKay, DM Dawson, C Kirst, JR Yates, TFG Green, ... Inorganic Chemistry 55 (21), 10881-10887, 2016 | 13 | 2016 |
Protein Structure Prediction from Amino Acid Sequences Using Self-Attention Neural Networks J Jumper, AW Senior, RA Evans, RJ Bates, M Figurnov, A Pritzel, ... US Patent App. 17/108,890, 2021 | | 2021 |
Population based training of neural networks ME Jaderberg, W Czarnecki, TFG Green, VC Dalibard US Patent App. 16/766,631, 2021 | | 2021 |