Membrane Clustering of Coronavirus Variants Using Document Similarity.
Genes (Basel)
; 13(11)2022 10 28.
Article
in English
| MEDLINE | ID: covidwho-2090055
ABSTRACT
Currently, as an effect of the COVID-19 pandemic, bioinformatics, genomics, and biological computations are gaining increased attention. Genomes of viruses can be represented by character strings based on their nucleobases. Document similarity metrics can be applied to these strings to measure their similarities. Clustering algorithms can be applied to the results of their document similarities to cluster them. P systems or membrane systems are computation models inspired by the flow of information in the membrane cells. These can be used for various purposes, one of them being data clustering. This paper studies a novel and versatile clustering method for genomes and the utilization of such membrane clustering models using document similarity metrics, which is not yet a well-studied use of membrane clustering models.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pandemics
/
COVID-19
Topics:
Variants
Limits:
Humans
Language:
English
Year:
2022
Document Type:
Article
Affiliation country:
Genes13111966
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