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CC BY V4.0, Open Access
Journal article
Drug-CoV: a drug-origin knowledge graph discovering drug repurposing targeting COVID-19
Knowledge and information systems
2023
Abstract
Drug repurposing is a technique for probing new usages of existing medicines, but its traditional methods, such as computational approaches, can be time-consuming and laborious. Recently, knowledge graphs (KGs) have emerged as a powerful approach for graph-based representation in drug repurposing, encoding entities and relations to predict new connections and facilitate drug discovery. As COVID-19 has become a major public health concern, it is critical to establish an appropriate COVID-19 KG for drug repurposing to combat the spread of the virus. However, most publicly available COVID-19 KGs lack support for multi-relations and comprehensive entity types. Moreover, none of them originates from COVID-19-related drugs, making it challenging to identify effective treatments. To tackle these issues, we developed Drug-CoV, a drug-origin and multi-relational COVID-19 KG. We evaluated the quality of Drug-CoV by performing link prediction and comparing the results to another publicly available COVID-19 KG. Our results showed that Drug-CoV outperformed the comparing KG in predicting new links between entities. Overall, Drug-CoV represents a valuable resource for COVID-19 drug repurposing efforts and demonstrates the potential of KGs for facilitating drug discovery.
Details
- Title
- Drug-CoV: a drug-origin knowledge graph discovering drug repurposing targeting COVID-19
- Authors/Creators
- Sirui Li - Murdoch University, School of Information TechnologyKok Wai Wong - Murdoch UniversityDengya Zhu - Curtin UniversityChun Che Fung - Murdoch University
- Publication Details
- Knowledge and information systems
- Publisher
- Springer
- Identifiers
- 991005593757507891
- Copyright
- © 2023 The Author(s)
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Citation topics
- 1 Clinical & Life Sciences
- 1.54 Molecular & Cell Biology - Genetics
- 1.54.79 Genomic Bioinformatics
- Web Of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- ESI research areas
- Computer Science