OntoRepliCov: an Ontology-Based Approach for Modeling the SARS-CoV-2 Replication Process.
Knowledge representation
SWRL
biology domain
reasoning process
Journal
Procedia computer science
ISSN: 1877-0509
Titre abrégé: Procedia Comput Sci
Pays: Netherlands
ID NLM: 101537771
Informations de publication
Date de publication:
2021
2021
Historique:
entrez:
11
10
2021
pubmed:
12
10
2021
medline:
12
10
2021
Statut:
ppublish
Résumé
Understanding the replication machinery of viruses contributes to suggest and try effective antiviral strategies. Exhaustive knowledge about the proteins structure, their function, or their interaction is one of the preconditions for successfully modeling it. In this context, modeling methods based on a formal representation with a high semantic expressiveness would be relevant to extract proteins and their nucleotide or amino acid sequences as an element from the replication process. Consequently, our approach relies on the use of semantic technologies to design the SARS-CoV-2 replication machinery. This provides the ability to infer new knowledge related to each step of the virus replication. More specifically, we developed an ontology-based approach enriched with reasoning process of a complete replication machinery process for SARS-CoV-2. We present in this paper a partial overview of our ontology OntoRepliCov to describe one step of this process, namely, the continuous translation or protein synthesis, through classes, properties, axioms, and SWRL (Semantic Web Rule Language) rules.
Identifiants
pubmed: 34630741
doi: 10.1016/j.procs.2021.08.050
pii: S1877-0509(21)01537-4
pmc: PMC8486259
doi:
Types de publication
Journal Article
Langues
eng
Pagination
487-496Informations de copyright
© 2021 The Author(s). Published by Elsevier B.V.
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