An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction
Antimicrobial resistance (AMR) poses a threat to global public health. To mitigate the impacts of AMR, it is important to identify the molecular mechanisms of AMR and thereby determine optimal therapy as early as possible. Conventional machine learning-based drug-resistance analyses assume genetic v...
| 主要な著者: | , , , , , , , |
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| フォーマット: | Journal article |
| 言語: | English |
| 出版事項: |
Oxford University Press
2021
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