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...

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Detalles Bibliográficos
Autores principales: Rancati, Simone, Nicora, Giovanna, Prosperi, Mattia, Bellazzi, Riccardo, Marini, Simone, Salemi, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
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

Internet

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

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