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Tracking SARS-CoV-2 Spike Protein Mutations in the United States (2020/01 – 2021/03) Using a Statistical Learning Strategy

2021-05-18

Abstract excerpt

BACKGROUND: The emergence and establishment of SARS-CoV-2 variants of interest (VOI) and variants of concern (VOC) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking Spike protein mutations potentially relevant to public health.<br><br>METHODS: We analyzed 189,284 Spike protein sequences from US COVID-19 cases, deposited...

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Literature Corpus work
56c0996c-c161-52cc-be53-85468a7d2b3d
DOI
10.2139/ssrn.3844900
Open publication

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Tracking SARS-CoV-2 Spike Protein Mutations in the United States (2020/01 – 2021/03) Using a Statistical Learning StrategyDOI 10.2139/ssrn.3844900
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