Using Optimal Sequencing Algorithms for COVID-19 Case Study

Jing Wei Heng, Filbert H. Juwono, Regina Reine

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2021 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665438650
DOIs
Publication statusPublished - 7 Jul 2021
Externally publishedYes
Event2021 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2021 - Virtual, Miri, Malaysia
Duration: 7 Jul 20219 Jul 2021

Publication series

Name2021 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2021

Conference

Conference2021 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2021
Country/TerritoryMalaysia
CityVirtual, Miri
Period7/07/219/07/21

Keywords

  • COVID-19
  • Needleman-Wunsh
  • SARS-Cov-2
  • Smith-Waterman
  • genome analysis
  • sequence alignment

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