reasoning over biomedical objects linked in knowledge oriented pathways

ROBOKOP is an open-source biomedical knowledge graph that integrates and semantically harmonizes important knowledge sources. ROBOKOP contains tens of millions of nodes representing entities such as genes, chemicals, and diseases, and hundreds of millions of edges representing the relationships between them. Here, users can query this integrated knowledge to explain connections between biomedical entities, and use the underlying integrated knowledge to rapidly deploy their own informatics tools.

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If you use ROBOKOP in your work, please cite the following papers:

  1. Bizon C, Cox S, Balhoff J, Kebede Y, Wang P, Morton K, Fecho K, Tropsha A. ROBOKOP KG and KGB: integrated knowledge graphs from federated sources. J Chem Inf Model 2019 Dec 23;59(12):4968–4973. doi: 10.1021/acs.jcim.9b00683.
  2. Morton K, Wang P, Bizon C, Cox S, Balhoff J, Kebede Y, Fecho K, Tropsha A. ROBOKOP: an abstraction layer and user interface for knowledge graphs to support question answering. Bioinformatics 2019;pii:btz604. doi: 10.1093/bioinformatics/btz604.


ROBOKOP is a joint creation of the Renaissance Computing Institute (RENCI) at the University of North Carolina at Chapel Hill and CoVar LLC. The prototype was developed with funding from the National Center for Advancing Translational Science, National Institutes of Health (award #OT2TR002514). ROBOKOP's continued development is supported with joint funding from the National Institute of Environmental Health Sciences and the Office of Data Science Strategy within the Institutes of Health (award #U24ES035214). ExEmPLAR is funded by XXX


ROBOKOP is available under the MIT license.


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