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Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders
The COVID-19 pandemic exemplified the need for a rapid, effective genomic-based surveillance system to predict emerging SARS-CoV-2 variants and lineages. Traditional molecular epidemiology methods, which leverage public health surveillance or integrated sequence data repositories, are able to charac...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Cold Spring Harbor Laboratory
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634784/ https://www.ncbi.nlm.nih.gov/pubmed/37961168 http://dx.doi.org/10.1101/2023.10.24.563721 |