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CoV2K model, a comprehensive representation of SARS-CoV-2 knowledge and data interplay
Tommaso Alfonsi1, Ruba Al Khalaf1, Stefano Ceri1
1Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, 20133, Milano, Italy.
Scientific Data
|June 1, 2022
Summary
The COVID-19 pandemic spurred extensive SARS-CoV-2 genome research, but data quality issues emerged. CoV2K, a new model, clarifies viral mutations and variant effects, integrating diverse data for better understanding.
Area of Science:
- Virology
- Genomics
- Bioinformatics
Background:
- The COVID-19 pandemic led to widespread SARS-CoV-2 genome sequencing and data sharing.
- Existing public resources for monitoring viral evolution present information quality challenges, including incompleteness and inconsistency.
Purpose of the Study:
- To introduce CoV2K, an abstract model designed to explain SARS-CoV-2 concepts and interactions.
- To focus on viral mutations, their co-occurrence within variants, and their functional effects.
- To drive data and knowledge integration by harmonizing information from multiple resources.
Main Methods:
- Development of an abstract model (CoV2K) for SARS-CoV-2 information.
- Implementation of CoV2K as a queryable graph database.
- Provision of a RESTful API for accessing entities and relationships within the graph.
Main Results:
- CoV2K offers a structured approach to understanding complex viral data.
- The model integrates information from disparate sources, addressing data quality issues.
- A graph-based representation and API facilitate exploration and querying of viral knowledge.
Conclusions:
- CoV2K provides a clear framework for navigating SARS-CoV-2 genomic information.
- The model aids in understanding viral evolution, mutations, and variant characteristics.
- CoV2K supports data harmonization and knowledge discovery in the context of the COVID-19 pandemic.
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