SARS-CoV-2 Bioinformatics: Mutation Sequence Analysis of the SARS-CoV-2 Virus Using Needleman-Wunsch Alignment, Boolean Logic, and the Kimura Model
Felza Ridho (*), Mohammad Isa Irawan

Department of Mathematics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS, Sukolilo, Surabaya, 60111, Indonesia.
(*)felzaridho98[at]gmail.com

Abstract

The SARS-CoV-2 virus, which has now become a pandemic, was discovered at the end of 2019. The consequences caused by this virus have been felt throughout the world. In addition to the virus that appeared at the beginning of 2019, various variants have appeared, ranging from the virus that appeared in the city of Wuhan to the omicron virus variant, with varying levels of virus malignancy. Virus variants are declared different if the genetic data in the form of DNA sequences has different elements. With the emergence of the SARS-CoV-2 virus variant and the spread of the virus, which is still ongoing today, it is necessary to carry out a process to find many mutations of the SARS-CoV-2 variant in the form of DNA sequences. In the process of looking for many mutations, Needleman-Wunsch alignment will be used, and Boolean logic will also be used to analyze the elements in the sequence one by one. The mutation sequence obtained will be used as a reference for a closeness analysis between variants of the SARS-CoV-2 virus by forming a distance evolution matrix with the Kimura model. The results obtained show the percentage of transition and transversion mutations between variants, where the mutation percentage and the farthest distance are in the Alpha and Eta variants with a distance of 4.21 and a mutation of 0.27856%, and the percentage and the shortest distance are in the variants from Wuhan and Lota with a distance of 3.14 and a mutation of 0.06688%.

Keywords: SARS-CoV-2, Needleman-Wunsch alignment, Boolean logic, Kimura Model

Topic: COMPUTATIONAL SCIENCES