Accès ouvert

Different genomic representations of novel pathogens base on signal processing algorithms: COVID-19 case study

Article scientifique 2022 Anglais

Résumé

Abstract Coronaviruses are a type of frequent RNA virus. They are responsible for digestive and respiratory infections in animal and human genomes. A coronavirus renamed COVID-19 appeared and spread in the world which makes it declared in March 2020 a pandemic by the World Health Organization. SARS-CoV-2 genome, responsible for COVID-19 virus, has a size equal to 29,903 nucleotides, and its genetic makeup is composed of 11 functional open reading frames (ORFs). This paper proposes comparison algorithms to find SARS-Cov2 origin using digital genomic signatures. As a result, the five closest genomes related to SARS-CoV-2 are RaTG13, Pangolin-cov-PCoV_GX-P2V, Pangolin CoV MP789, bat-SL-CoVZC45 and bat-SL-CoVZXC21.

Citer ce document

Touati, R., Touati, M., Benzarti, F., Kumar, V., Kharrat, M., Elngar, A. (2022). Different genomic representations of novel pathogens base on signal processing algorithms: COVID-19 case study. https://doi.org/10.21203/rs.3.rs-1743456/v1

Accès au document

Voir sur le dépôt source

Ce document est hébergé sur son dépôt institutionnel d'origine.

Auteur(s)

Rabeb Touati Mohamed Touati Faouzi Benzarti Vishal Kumar Maher Kharrat Ahmed A. Elngar

Statistiques

Consultations : 1

Téléchargements : 0