Randomness for Nucleotide Sequences of SARS-CoV-2 and Its Related Subfamilies

• Main Author: Ray-Ming Chen
• Format: Article
• Language: English
• Published: Hindawi Limited 2020-01-01
• Series: Computational and Mathematical Methods in Medicine
• Online Access: http://dx.doi.org/10.1155/2020/8819942

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.