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Data mining of coronavirus: SARS-CoV-2, SARS-CoV and MERS-CoV

Authors
  • Huh, Jung Eun1
  • Han, Seunghee2
  • Yoon, Taeseon3
  • 1 University of Oxford, Oxford, UK , Oxford (United Kingdom)
  • 2 University of Birmingham, Birmingham, UK , Birmingham (United Kingdom)
  • 3 Korea University, Seoul, South Korea , Seoul (South Korea)
Type
Published Article
Journal
BMC Research Notes
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Apr 20, 2021
Volume
14
Issue
1
Identifiers
DOI: 10.1186/s13104-021-05561-4
Source
Springer Nature
Keywords
License
Green

Abstract

ObjectiveIn this study we compare the amino acid and codon sequence of SARS-CoV-2, SARS-CoV and MERS-CoV using different statistics programs to understand their characteristics. Specifically, we are interested in how differences in the amino acid and codon sequence can lead to different incubation periods and outbreak periods. Our initial question was to compare SARS-CoV-2 to different viruses in the coronavirus family using BLAST program of NCBI and machine learning algorithms.ResultsThe result of experiments using BLAST, Apriori and Decision Tree has shown that SARS-CoV-2 had high similarity with SARS-CoV while having comparably low similarity with MERS-CoV. We decided to compare the codons of SARS-CoV-2 and MERS-CoV to see the difference. Though the viruses are very alike according to BLAST and Apriori experiments, SVM proved that they can be effectively classified using non-linear kernels. Decision Tree experiment proved several remarkable properties of SARS-CoV-2 amino acid sequence that cannot be found in MERS-CoV amino acid sequence. The consequential purpose of this paper is to minimize the damage on humanity from SARS-CoV-2. Hence, further studies can be focused on the comparison of SARS-CoV-2 virus with other viruses that also can be transmitted during latent periods.

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