Abstract
This paper presents a statistical genomic analysis of the three major coronaviruses that have caused outbreaks in history, the SARS-CoV, MERS-CoV and SARS-CoV-2. Fasta files of the isolated genomes of these viruses were used to perform a global pairwise alignment in Biopython in order to establish sequence identity and the possibility of similar origins. These were then translated into functional proteins and tested for statistically significant differences in aromaticities, instability indices and isoelectric points using ANOVAs and Tukey-HSD post-hoc tests. This research will help future researchers in understanding the characteristics of the SARS-CoV-2 (the new virus strain that has caused the COVID-19 pandemic) and the properties that distinguish it from the MERS-CoV and SARS-CoV.
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Sharma, M. (2021). Statistical Genomic Analysis of the SARS-CoV, MERS-CoV and SARS-CoV-2. In: Hassanien, A.E., Bhattacharyya, S., Chakrabati, S., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 1300. Springer, Singapore. https://doi.org/10.1007/978-981-33-4367-2_52
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DOI: https://doi.org/10.1007/978-981-33-4367-2_52
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