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.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1107/S2059798323004928 | DOI Listing |
Publication Analysis
Top Keywords
structural biology
8
alphafold future
4
future structural
4
biology editorial
4
editorial acknowledges
4
acknowledges transformative
4
transformative impact
4
impact machine-learning
4
machine-learning methods
4
methods alphafold
4
Similar Publications
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!