Author: Heng, J. W.; Juwono, F. H.; Reine, R.
Title: Using Optimal Sequencing Algorithms for COVID-19 Case Study Cord-id: y2c5ncrm Document date: 2021_1_1
ID: y2c5ncrm
Snippet: The World Health Organization (WHO) announced coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, a pandemic in 2020. The virus has undergone some mutation, making disease detection and treatment more difficult. In this paper, we review several sequence alignment algorithms which can be used to compare and observe the genome sequences. We compare three SARS-CoV-2 virus genomes obtained from Wuhan, Illinois, and India using Needleman-Wunsch and Smith-Waterman algorithms. The results s
Document: The World Health Organization (WHO) announced coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, a pandemic in 2020. The virus has undergone some mutation, making disease detection and treatment more difficult. In this paper, we review several sequence alignment algorithms which can be used to compare and observe the genome sequences. We compare three SARS-CoV-2 virus genomes obtained from Wuhan, Illinois, and India using Needleman-Wunsch and Smith-Waterman algorithms. The results show that there are several misalignment nucleotide sequences, inferring that there are mutations in the SARS-Cov-2 virus found in the Illinois and India. © 2021 IEEE.
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