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OntoRepliCov: an Ontology-Based Approach for Modeling the SARS-CoV-2 Replication Process
Wissame Laddada1,2, Lina F Soualmia1, Cecilia Zanni-Merk1
1Normandie Universit, LITIS, 7600 Rouen, France.
Procedia Computer Science
|October 11, 2021
Summary
This study introduces OntoRepliCov, an ontology for modeling the SARS-CoV-2 replication machinery. It uses semantic technologies to infer new knowledge about viral protein synthesis and replication steps.
Area of Science:
- Virology
- Bioinformatics
- Semantic Web Technologies
Background:
- Understanding viral replication is crucial for developing antiviral strategies.
- Accurate modeling of viral proteins, their functions, and interactions is a prerequisite for effective drug design.
- Formal representations with high semantic expressiveness are needed to model complex biological processes like viral replication.
Purpose of the Study:
- To design a formal model of the SARS-CoV-2 replication machinery using semantic technologies.
- To develop an ontology-based approach for inferring new knowledge about each step of viral replication.
- To present a partial overview of the OntoRepliCov ontology, focusing on the continuous translation (protein synthesis) step.
Main Methods:
- Utilized semantic technologies to create a formal representation of the SARS-CoV-2 replication machinery.
- Developed an ontology (OntoRepliCov) incorporating classes, properties, and axioms.
- Employed Semantic Web Rule Language (SWRL) rules for reasoning processes within the ontology.
- Focused on modeling the continuous translation or protein synthesis stage of viral replication.
Main Results:
- Successfully designed an ontology-based model for the SARS-CoV-2 replication machinery.
- Demonstrated the capability to infer new knowledge related to viral replication steps.
- Provided a detailed description of the continuous translation process within the OntoRepliCov ontology.
- Established a foundation for comprehensive modeling of the entire SARS-CoV-2 replication cycle.
Conclusions:
- OntoRepliCov provides a robust framework for understanding and modeling the SARS-CoV-2 replication machinery.
- The ontology facilitates knowledge discovery and inference in viral biology.
- This semantic approach enhances the potential for developing targeted antiviral therapies by improving our understanding of viral processes.
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