SARS-CoV-2 Omicron Variant Genomic Sequences and Their Epidemiological Correlates Regarding the End of the Pandemic: In Silico Analysis

Kumar, A., Asghar, A., Singh, H. N., Faiq, M. A., Kumar, S., Narayan, R. K., Kumar, G., Dwivedi, P., Sahni, C., Jha, R. K., Kulandhasamy, M., Prasoon, P., Sesham, K., Kant, K., & Pandey, S. N. (2023). SARS-CoV-2 Omicron Variant Genomic Sequences and Their Epidemiological Correlates Regarding the End of the Pandemic: In Silico Analysis. JMIR Bioinformatics and Biotechnology, 4, e42700. https://doi.org/10.2196/42700
Authors:
Ashutosh Kumar
Adil Asghar
Himanshu Narayan Singh
Muneeb A. Faiq
Sujeet Kumar
Ravi Kant Narayan
Gopichand Kumar
Prakhar Dwivedi
Chetan Sahni
Rakesh Kumar Jha
Maheswari Kulandhasamy
Pranav Prasoon
Kishore Sesham
Kamla Kant
Sada N. Pandey
Affiliated Authors:
Himanshu Narayan Singh
Columbia Affiliation:
Subjects:
Coronavirus Disease 2019 Research (OpenAlex Topic)
Diagnostic Methods for COVID-19 Detection (OpenAlex Topic)
Coronavirus Disease 2019 (OpenAlex Topic)
Author Keywords:
covid-19
omicron
data
epidemiology
genomic
immune escape
mutations
pandemic
policy
transmissibility
transmission
variants
virulence
virus
elink
Publication Type:
Article
Unique ID:
10.2196/42700
PMID:
36688013
DOI:
10.2196/42700
Journal:
JMIR Bioinformatics and Biotechnology
Publication Date:
Data Source:
OpenAlex
Source Link:
View OpenAlex Record
View PubMed Record

Record Created: