Application of Statistical Learning to Identify Omicron Mutations in SARS-CoV-2 Viral Genome Sequence Data From Populations in Africa and the United States

IMPORTANCE: With timely collection of SARS-CoV-2 viral genome sequences, it is important to apply efficient data analytics to detect emerging variants at the earliest time. OBJECTIVE: To evaluate the application of a statistical learning strategy (SLS) to improve early detection of novel SARS-CoV-2...

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Detalles Bibliográficos
Autores principales: Zhao, Lue Ping, Lybrand, Terry P., Gilbert, Peter, Madeleine, Margaret, Payne, Thomas H., Cohen, Seth, Geraghty, Daniel E., Jerome, Keith R., Corey, Lawrence
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2022
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453543/
https://www.ncbi.nlm.nih.gov/pubmed/36069983
http://dx.doi.org/10.1001/jamanetworkopen.2022.30293

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453543/
https://www.ncbi.nlm.nih.gov/pubmed/36069983
http://dx.doi.org/10.1001/jamanetworkopen.2022.30293

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