AlphaFold and the future of structural biology
This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology.
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
International Union of Crystallography
2023-07-01
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| Series: | IUCrJ |
| Subjects: | |
| Online Access: | http://scripts.iucr.org/cgi-bin/paper?S2052252523004943 |
| Summary: | This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology. |
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| ISSN: | 2052-2525 |