SARSMutOnto: An Ontology for SARS-CoV-2 Lineages and Mutations

Article Subjects > Biomedicine Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
Abierto Inglés Mutations allow viruses to continuously evolve by changing their genetic code to adapt to the hosts they infect. It is an adaptive and evolutionary mechanism that helps viruses acquire characteristics favoring their survival and propagation. The COVID-19 pandemic declared by the WHO in March 2020 is caused by the SARS-CoV-2 virus. The non-stop adaptive mutations of this virus and the emergence of several variants over time with characteristics favoring their spread constitute one of the biggest obstacles that researchers face in controlling this pandemic. Understanding the mutation mechanism allows for the adoption of anticipatory measures and the proposal of strategies to control its propagation. In this study, we focus on the mutations of this virus, and we propose the SARSMutOnto ontology to model SARS-CoV-2 mutations reported by Pango researchers. A detailed description is given for each mutation. The genes where the mutations occur and the genomic structure of this virus are also included. The sub-lineages and the recombinant sub-lineages resulting from these mutations are additionally represented while maintaining their hierarchy. We developed a Python-based tool to automatically generate this ontology from various published Pango source files. At the end of this paper, we provide some examples of SPARQL queries that can be used to exploit this ontology. SARSMutOnto might become a ‘wet bench’ machine learning tool for predicting likely future mutations based on previous mutations. metadata Bakkas, Jamal and Hanine, Mohamed and Chekry, Abderrahman and Gounane, Said and de la Torre Díez, Isabel and Lipari, Vivian and Martínez López, Nohora Milena and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, nohora.martinez@uneatlantico.es, UNSPECIFIED (2023) SARSMutOnto: An Ontology for SARS-CoV-2 Lineages and Mutations. Viruses, 15 (2). p. 505. ISSN 1999-4915

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Abstract

Mutations allow viruses to continuously evolve by changing their genetic code to adapt to the hosts they infect. It is an adaptive and evolutionary mechanism that helps viruses acquire characteristics favoring their survival and propagation. The COVID-19 pandemic declared by the WHO in March 2020 is caused by the SARS-CoV-2 virus. The non-stop adaptive mutations of this virus and the emergence of several variants over time with characteristics favoring their spread constitute one of the biggest obstacles that researchers face in controlling this pandemic. Understanding the mutation mechanism allows for the adoption of anticipatory measures and the proposal of strategies to control its propagation. In this study, we focus on the mutations of this virus, and we propose the SARSMutOnto ontology to model SARS-CoV-2 mutations reported by Pango researchers. A detailed description is given for each mutation. The genes where the mutations occur and the genomic structure of this virus are also included. The sub-lineages and the recombinant sub-lineages resulting from these mutations are additionally represented while maintaining their hierarchy. We developed a Python-based tool to automatically generate this ontology from various published Pango source files. At the end of this paper, we provide some examples of SPARQL queries that can be used to exploit this ontology. SARSMutOnto might become a ‘wet bench’ machine learning tool for predicting likely future mutations based on previous mutations.

Item Type: Article
Uncontrolled Keywords: ontology; genome structure; SARS-CoV-2; mutation; lineage
Subjects: Subjects > Biomedicine
Divisions: Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
Date Deposited: 01 Mar 2023 23:30
Last Modified: 01 Mar 2023 23:30
URI: https://repositorio.unincol.edu.co/id/eprint/6097

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Human‐based new approach methodologies to accelerate advances in nutrition research

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