Detection of spike protein mutation in SARS-CoV-2 variants of concern with support vector classification over (d,r,p)-layer coordinate system
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Creator Supot Hannongbua
Title Detection of spike protein mutation in SARS-CoV-2 variants of concern with support vector classification over (d,r,p)-layer coordinate system
Contributor Kabin Kanjamapornkul, Thanyada Rungrotmongkol
Publisher Faculty of Science, Ubon Ratchathani University
Publication Year 2565
Journal Title Journal of Science and Science Education
Journal Vol. 5
Journal No. 1
Page no. 58-71
Keyword Chern-Simons Current, Genotype, SARS-CoV-2, Support Vector Machine
URL Website https://so04.tci-thaijo.org/index.php/JSSE
Website title https://so04.tci-thaijo.org/index.php/JSSE/article/view/255550/174624
ISSN ISSN 2697-410X
Abstract Quantitative measurement of the quantum genotype of mutated amino acids in the S protein on different variants of SARS-CoV-2 was performed with Chern-Simons current. The Chern-Simons current in our proposed novel approach was used to plot the curvature of S protein folding based on mirror symmetry and add more extra properties of central dogma in biology. The Yang-Mills field in genetic code is an induced curl operator of parallel transport of unified field between hydrogen bonding between 3 types of biomolecules over the Lagrangian system in (d,r,p)-layer coordinate system on a tangent of the four-dimensional manifold defined by the surface of behavior field in twisted torus spanned by four nitrogen bases of A, T, C, and G. The empirical analysis of quantum genotype of S protein between 17 January 2020 and 30 June 2021 was reported in the histogram with left shift. The prediction of the genetic variation in S protein of various variants of interest and variants of concern in SARS-CoV-2 were computed by using a machine learning algorithm based on support vector classification over the fitting parameter of the quantum genotype with good performance.
Faculty of Science, Ubon Ratchathani University

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