Learning patterns of HIV-1 resistance to broadly neutralizing antibodies with reduced subtype bias using multi-task learning
The ability to predict HIV-1 resistance to broadly neutralizing antibodies (bnAbs) will increase bnAb therapeutic benefits. Machine learning is a powerful approach for such prediction. One challenge is that some HIV-1 subtypes in currently available training datasets are underrepresented, which like...
| Autors principals: | , , , , , , |
|---|---|
| Format: | Journal article |
| Idioma: | English |
| Publicat: |
Public Library of Science
2024
|