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COVID-KOP: Integrating Emerging COVID-19 Data with the ROBOKOP Database
Daniel Korn1, Tesia Bobrowski2, Michael Li1
1Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7568, USA.
Chemrxiv : the Preprint Server for Chemistry
|July 1, 2020
Summary
A new COVID-19 knowledgebase, COVID-KOP, integrates biomedical data and literature to aid drug repurposing research. This tool helps test hypotheses for new COVID-19 treatments using existing and candidate drugs.
Area of Science:
- Biomedical Informatics
- Computational Biology
- Drug Discovery
Background:
- The COVID-19 pandemic necessitates rapid identification of therapeutic strategies.
- Existing biomedical knowledge graphs require integration with emerging pandemic-specific data.
- Drug repurposing offers a promising avenue for accelerating treatment development.
Approach:
- Developed COVID-KOP by integrating the ROBOKOP biomedical knowledge graph with COVID-19 literature from the CORD-19 collection.
- Annotated CORD-19 literature to enrich the knowledge base with disease-specific information.
- Designed COVID-KOP for hypothesis testing related to drug repurposing against SARS-CoV-2.
Key Points:
- COVID-KOP unifies diverse biomedical information sources relevant to COVID-19.
- Facilitates the exploration of known drugs and clinical candidates for repurposing.
- Enables hypothesis generation for novel therapeutic interventions against COVID-19.
Conclusions:
- COVID-KOP provides a valuable resource for researchers investigating COVID-19 therapeutics.
- The knowledgebase supports efficient hypothesis testing for drug repurposing.
- Accessible online, COVID-KOP promotes collaborative research in combating the pandemic.
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