Jones, DT;
Thornton, JM;
(2022)
The impact of AlphaFold2 one year on.
Nature Methods
, 19
(1)
pp. 15-20.
10.1038/s41592-021-01365-3.
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Abstract
The greatly improved prediction of protein 3D structure from sequence achieved by the second version of AlphaFold in 2020 has already had a huge impact on biological research, but challenges remain; the protein folding problem cannot be considered solved. We expect fierce competition to improve the method even further and new applications of machine learning to help illuminate proteomes and their many interactions.
| Type: | Article |
|---|---|
| Title: | The impact of AlphaFold2 one year on |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41592-021-01365-3 |
| Publisher version: | https://doi.org/10.1038/s41592-021-01365-3 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10142031 |
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