COVID-KOP: integrating emerging COVID-19 data with the ROBOKOP database

Daniel Korn; Tesia Bobrowski; Michael Li; Yaphet Kebede; Patrick Wang; Phillips Owen; Gaurav Vaidya; Eugene Muratov; Rada Chirkova; Chris Bizon; Alexander Tropsha

doi:10.1093/bioinformatics/btaa718

COVID-KOP: integrating emerging COVID-19 data with the ROBOKOP database

Bioinformatics. 2021 May 1;37(4):586-587. doi: 10.1093/bioinformatics/btaa718.

Authors

Affiliations

¹ Department of Computer Science, University of North Carolina at Chapel Hill, USA.
² Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, USA.
³ Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7568, USA.
⁴ CoVar Applied Technologies, Durham, NC 27701, USA.
⁵ Department of Computer Science, North Carolina State University, Raleigh, NC 27606-5550, USA.

Abstract

Summary: In response to the COVID-19 pandemic, we established COVID-KOP, a new knowledgebase integrating the existing Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP) biomedical knowledge graph with information from recent biomedical literature on COVID-19 annotated in the CORD-19 collection. COVID-KOP can be used effectively to generate new hypotheses concerning repurposing of known drugs and clinical drug candidates against COVID-19 by establishing respective confirmatory pathways of drug action.

Availability and implementation: COVID-KOP is freely accessible at https://covidkop.renci.org/. For code and instructions for the original ROBOKOP, see: https://github.com/NCATS-Gamma/robokop.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

COVID-19*
Databases, Factual
Humans
Knowledge Bases
Pandemics
SARS-CoV-2

Abstract

Publication types

MeSH terms

Grants and funding