Tim Green
Tim Green
Google DeepMind
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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
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
The kinetics human action video dataset
W Kay, J Carreira, K Simonyan, B Zhang, C Hillier, S Vijayanarasimhan, ...
arXiv preprint arXiv:1705.06950, 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
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
Protein complex prediction with AlphaFold-Multimer
R Evans, M O’Neill, A Pritzel, N Antropova, A Senior, T Green, A Žídek, ...
biorxiv, 2021.10. 04.463034, 2021
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
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
Population based training of neural networks
M Jaderberg, V Dalibard, S Osindero, WM Czarnecki, J Donahue, ...
arXiv preprint arXiv:1711.09846, 2017
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
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
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
Accurate structure prediction of biomolecular interactions with AlphaFold 3
J Abramson, J Adler, J Dunger, R Evans, T Green, A Pritzel, ...
Nature, 1-3, 2024
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
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
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
AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences
M Varadi, D Bertoni, P Magana, U Paramval, I Pidruchna, ...
Nucleic acids research 52 (D1), D368-D375, 2024
Relativistic nuclear magnetic resonance J-coupling with ultrasoft pseudopotentials and the zeroth-order regular approximation
TFG Green, JR Yates
J. Chem. Phys., 234106, 2014
Computational predictions of protein structures associated with COVID-19
J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, the AlphaFold team
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
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Artículos 1–20