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 | 29591 | 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 | 5745 | 2022 |
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 | 3416 | 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 | 2399 | 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 | 2346 | 2021 |
Atomic-level characterization of the structural dynamics of proteins DE Shaw, P Maragakis, K Lindorff-Larsen, S Piana, RO Dror, ... Science 330 (6002), 341-346, 2010 | 2092 | 2010 |
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 | 1560 | 2024 |
Effective gene expression prediction from sequence by integrating long-range interactions Ž Avsec, V Agarwal, D Visentin, JR Ledsam, A Grabska-Barwinska, ... Nature methods 18 (10), 1196-1203, 2021 | 738 | 2021 |
Accurate proteome-wide missense variant effect prediction with AlphaMissense J Cheng, G Novati, J Pan, C Bycroft, A Žemgulytė, T Applebaum, A Pritzel, ... Science 381 (6664), eadg7492, 2023 | 616 | 2023 |
Oncogenic mutations counteract intrinsic disorder in the EGFR kinase and promote receptor dimerization Y Shan, MP Eastwood, X Zhang, ET Kim, A Arkhipov, RO Dror, J Jumper, ... Cell 149 (4), 860-870, 2012 | 416 | 2012 |
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 | 346 | 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 | 337 | 2021 |
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 | 308 | 2024 |
Accelerating large language model decoding with speculative sampling C Chen, S Borgeaud, G Irving, JB Lespiau, L Sifre, J Jumper arXiv preprint arXiv:2302.01318, 2023 | 246 | 2023 |
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 | 232* | 2020 |
Innovative scattering analysis shows that hydrophobic disordered proteins are expanded in water JA Riback, MA Bowman, AM Zmyslowski, CR Knoverek, JM Jumper, ... Science 358 (6360), 238-241, 2017 | 222 | 2017 |
Protein structure predictions to atomic accuracy with AlphaFold J Jumper, D Hassabis Nature methods 19 (1), 11-12, 2022 | 185 | 2022 |
Highly accurate protein structure prediction with AlphaFold., 2021, 596 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... DOI: https://doi. org/10.1038/s41586-021-03819-2, 583-589, 0 | 163 | |
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 | 154 | 2018 |
Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations MC Baxa, EJ Haddadian, JM Jumper, KF Freed, TR Sosnick Proceedings of the National Academy of Sciences 111 (43), 15396-15401, 2014 | 123 | 2014 |