Cargando…
Tracking SARS-CoV-2 Spike Protein Mutations in the United States (January 2020—March 2021) Using a Statistical Learning Strategy
The emergence and establishment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of interest (VOIs) and variants of concern (VOCs) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking...
Autores principales: | Zhao, Lue Ping, Lybrand, Terry P., Gilbert, Peter B., Hawn, Thomas R., Schiffer, Joshua T., Stamatatos, Leonidas, Payne, Thomas H., Carpp, Lindsay N., Geraghty, Daniel E., Jerome, Keith R. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777887/ https://www.ncbi.nlm.nih.gov/pubmed/35062214 http://dx.doi.org/10.3390/v14010009 |
Ejemplares similares
-
Tracking SARS-CoV-2 Spike Protein Mutations in the United States (2020/01 – 2021/03) Using a Statistical Learning Strategy
por: Zhao, Lue Ping, et al.
Publicado: (2021) -
Rapidly Identifying New Coronavirus Mutations of Potential Concern in the Omicron Variant Using an Unsupervised Learning Strategy
por: Zhao, Lue Ping, et al.
Publicado: (2022) -
Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy
por: Zhao, Lue Ping, et al.
Publicado: (2022) -
Application of Statistical Learning to Identify Omicron Mutations in SARS-CoV-2 Viral Genome Sequence Data From Populations in Africa and the United States
por: Zhao, Lue Ping, et al.
Publicado: (2022) -
CRD Editor’s Corner Archive: January–March 2021
por: Steiner, Michael C
Publicado: (2021)