Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods
Since its emergence in late 2019, SARS-CoV-2 has diversified into a large number of lineages and caused multiple waves of infection globally. Novel lineages have the potential to spread rapidly and internationally if they have higher intrinsic transmissibility and/or can evade host immune responses,...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
National Academy of Sciences
2024
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