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‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures
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“AlphaFold has combined numerous deep learning innovations to predict the three-dimensional (3D) structures of proteins at or near experimental scale resolution”
From AlphaFold, Artificial Intelligence (AI), and Allostery (2022) · cites this paper as [3]
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Metadata
- Authors
- Callaway, E.
- Corresponding author
- Callaway, Ewen
- Venue
- Nature
- Published
- 2020-11-30
- Volume
- 588
- Issue
- 7837
- Pages
- 203-204
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3108943181
- Cited by
- 499
- References
- 0
- Citations by year
- 2026: 15 · 2025: 39 · 2024: 77 · 2023: 87 · 2022: 97 · 2021: 181 · 2020: 2
- Type
- other
- Language
- en
- Open access
- closed
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- DeepMind, AlphaFold, protein structure prediction, protein 3D structure, deep learning, artificial intelligence in biology, protein folding
- MeSH terms
- Deep Learning, Models, Molecular, Protein Conformation, Proteins, Time Factors, Crystallography, X-Ray, Caspases
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