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...
| Những tác giả chính: | , , , , , , |
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| Định dạng: | Journal article |
| Ngôn ngữ: | English |
| Được phát hành: |
Public Library of Science
2024
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