A predictive language model for SARS-CoV-2 evolution
Abstract Modeling and predicting mutations are critical for COVID-19 and similar pandemic preparedness. However, existing predictive models have yet to integrate the regularity and randomness of viral mutations with minimal data requirements. Here, we develop a non-demanding language model utilizing...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2024-12-01
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| Series: | Signal Transduction and Targeted Therapy |
| Online Access: | https://doi.org/10.1038/s41392-024-02066-x |
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