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Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes

Virus attacks have had devastating effects on mankind. The prominent viruses such as Ebola virus (2012), SARS-CoV or Severe acute respiratory syndrome, Middle East respiratory syndrome-related coronavirus called as the MERS (EMC/2012), Spanish flu (H1N1 virus-1918) and the most recent COVID-19(SARS-...

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Autores principales: Purohit, Sidharth, Satapathy, Suresh Chandra, Sibi Chakkaravarthy, S, Zhang, Yu-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221988/
https://www.ncbi.nlm.nih.gov/pubmed/34189012
http://dx.doi.org/10.1007/s13369-021-05811-4
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author Purohit, Sidharth
Satapathy, Suresh Chandra
Sibi Chakkaravarthy, S
Zhang, Yu-Dong
author_facet Purohit, Sidharth
Satapathy, Suresh Chandra
Sibi Chakkaravarthy, S
Zhang, Yu-Dong
author_sort Purohit, Sidharth
collection PubMed
description Virus attacks have had devastating effects on mankind. The prominent viruses such as Ebola virus (2012), SARS-CoV or Severe acute respiratory syndrome, Middle East respiratory syndrome-related coronavirus called as the MERS (EMC/2012), Spanish flu (H1N1 virus-1918) and the most recent COVID-19(SARS-CoV-2) are the ones that have created a difficult situation for the survival of the human race. Currently, throughout the world, a global pandemic situation has put economy, livelihood and human existence in a very pathetic situation. Most of the above-mentioned viruses exhibit some similar characteristics and genetic pattern. Analysing such characteristics and genetic pattern can help the researchers to get a deeper insight into the viruses and helps in finding appropriate medicine or cure. To address these issues, this paper proposes an experimental analysis of the above-mentioned viruses data using correlation methods. The virus data considered for the experimental analysis include the distribution of various amino acids, protein sequences, 3D modelling of viruses, pairwise alignment of proteins that comprise the DNA genome of the viruses. Furthermore, this comparative analysis can be used by the researchers and organizations like WHO(World Health Organization), computational biologists, genetic engineers to frame a layout for studying the DNA sequence distribution, percentage of GC (guanine–cytosine) protein which determines the heat stability of viruses. We have used the Biopython to illustrate the gene study of prominent viruses and have derived results and insights in the form of 3D modelling. The experimental results are more promising with an accuracy rate of 96% in overall virus relationship calculation.
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spelling pubmed-82219882021-06-25 Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes Purohit, Sidharth Satapathy, Suresh Chandra Sibi Chakkaravarthy, S Zhang, Yu-Dong Arab J Sci Eng RESEARCH ARTICLE - SPECIAL ISSUE - AI based health-related Computing for COVID-19 (AIHRC) Virus attacks have had devastating effects on mankind. The prominent viruses such as Ebola virus (2012), SARS-CoV or Severe acute respiratory syndrome, Middle East respiratory syndrome-related coronavirus called as the MERS (EMC/2012), Spanish flu (H1N1 virus-1918) and the most recent COVID-19(SARS-CoV-2) are the ones that have created a difficult situation for the survival of the human race. Currently, throughout the world, a global pandemic situation has put economy, livelihood and human existence in a very pathetic situation. Most of the above-mentioned viruses exhibit some similar characteristics and genetic pattern. Analysing such characteristics and genetic pattern can help the researchers to get a deeper insight into the viruses and helps in finding appropriate medicine or cure. To address these issues, this paper proposes an experimental analysis of the above-mentioned viruses data using correlation methods. The virus data considered for the experimental analysis include the distribution of various amino acids, protein sequences, 3D modelling of viruses, pairwise alignment of proteins that comprise the DNA genome of the viruses. Furthermore, this comparative analysis can be used by the researchers and organizations like WHO(World Health Organization), computational biologists, genetic engineers to frame a layout for studying the DNA sequence distribution, percentage of GC (guanine–cytosine) protein which determines the heat stability of viruses. We have used the Biopython to illustrate the gene study of prominent viruses and have derived results and insights in the form of 3D modelling. The experimental results are more promising with an accuracy rate of 96% in overall virus relationship calculation. Springer Berlin Heidelberg 2021-06-24 /pmc/articles/PMC8221988/ /pubmed/34189012 http://dx.doi.org/10.1007/s13369-021-05811-4 Text en © King Fahd University of Petroleum & Minerals 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle RESEARCH ARTICLE - SPECIAL ISSUE - AI based health-related Computing for COVID-19 (AIHRC)
Purohit, Sidharth
Satapathy, Suresh Chandra
Sibi Chakkaravarthy, S
Zhang, Yu-Dong
Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes
title Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes
title_full Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes
title_fullStr Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes
title_full_unstemmed Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes
title_short Correlation-Based Analysis of COVID-19 Virus Genome Versus Other Fatal Virus Genomes
title_sort correlation-based analysis of covid-19 virus genome versus other fatal virus genomes
topic RESEARCH ARTICLE - SPECIAL ISSUE - AI based health-related Computing for COVID-19 (AIHRC)
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221988/
https://www.ncbi.nlm.nih.gov/pubmed/34189012
http://dx.doi.org/10.1007/s13369-021-05811-4
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