Title of article :
Randomness for Nucleotide Sequences of SARS-CoV-2 and Its Related Subfamilies
Author/Authors :
Chen, Ray-Ming School of Mathematics and Statistics - Baise University - Zhongshan - Guangxi Province, China
Abstract :
The origin and evolution of SARS-CoV-2 has been an important issue in tackling COVID-19. Research on these topics would
enhance our knowledge of this virus and help us develop vaccines or predict its paths of mutations. There are many theoretical
and clinical researches in this area. In this article, we devise a structural metric which directly measures the structural differences
between any two nucleotide sequences. In order to explore the mechanisms of how the evolution works, we associate the
nucleotide sequences of SARS-CoV-2 and its related families with the degrees of randomness. Since the distances between
randomly generated nucleotide sequences are very concentrated around a mean with low variance, they are qualified as good
candidates for the fundamental reference. Such reference could then be applied to measure the randomness of other
Coronaviridae sequences. Our findings show that the relative randomness ratios are very consistent and concentrated. This
result indicates their randomness is very stable and predictable. The findings also reveal the evolutional behaviours between the
Coronaviridae and all its subfamilies.
Keywords :
SARS-CoV-2 , COVID-19 , MERS-CoV
Journal title :
Computational and Mathematical Methods in Medicine