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Understanding mutation hotspots for the SARS-CoV-2 spike protein using Shannon Entropy and K-means c...

Understanding mutation hotspots for the SARS-CoV-2 spike protein using Shannon Entropy and K-means c...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8492016

Understanding mutation hotspots for the SARS-CoV-2 spike protein using Shannon Entropy and K-means clustering

About this item

Full title

Understanding mutation hotspots for the SARS-CoV-2 spike protein using Shannon Entropy and K-means clustering

Publisher

United States: Elsevier Ltd

Journal title

Computers in biology and medicine, 2021-11, Vol.138, p.104915-104915, Article 104915

Language

English

Formats

Publication information

Publisher

United States: Elsevier Ltd

More information

Scope and Contents

Contents

AbstractThe SARS-CoV-2 virus like many other viruses has transformed in a continual manner to give rise to new variants by means of mutations commonly through substitutions and indels. These mutations in some cases can give the virus a survival advantage making the mutants dangerous. In general, laboratory investigation must be carried to determine...

Alternative Titles

Full title

Understanding mutation hotspots for the SARS-CoV-2 spike protein using Shannon Entropy and K-means clustering

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8492016

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8492016

Other Identifiers

ISSN

0010-4825,1879-0534

E-ISSN

1879-0534

DOI

10.1016/j.compbiomed.2021.104915

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