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. 2019 Dec 23;59(12):4968-4973.
doi: 10.1021/acs.jcim.9b00683. Epub 2019 Dec 12.

ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources

Chris Bizon  1 , Steven Cox  1 , James Balhoff  1 , Yaphet Kebede  1 , Patrick Wang  2 , Kenneth Morton  2 , Karamarie Fecho  1 , Alexander Tropsha  3
Affiliations

ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources

Chris Bizon et al. J Chem Inf Model. .

Abstract

A proliferation of data sources has led to the notional existence of an implicit Knowledge Graph (KG) that contains vast amounts of biological knowledge contributed by distributed Application Programming Interfaces (APIs). However, challenges arise when integrating data across multiple APIs due to incompatible semantic types, identifier schemes, and data formats. We present ROBOKOP KG ( http://robokopkg.renci.org ), which is a KG that was initially built to support the open biomedical question-answering application, ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways) ( http://robokop.renci.org ). Additionally, we present the ROBOKOP Knowledge Graph Builder (KGB), which constructs the KG and provides an extensible framework to handle graph query over and integration of federated data sources.

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Figures

Figure 1.
Figure 1.
A graphical representation of a complex cypher query of the ROBOKOP KG. The query (available in the user guide at robokopkg.renci.org) searches for potential treatments for IBS by looking for drugs that act on disease-related genes in a manner that is opposite to that of disease-contributing chemical substances.
Figure 2.
Figure 2.
A graphical representation of a complex cypher query of the ROBOKOP KG. The query (available in the user guide at robokopkg.renci.org) looks for putative rare disease treatments among treatments for biologically-related common diseases, i.e., common diseases that share both a gene and a biological process with the input rare disease.
Figure 3.
Figure 3.
One of the top answer subgraphs returned by ROBOKOP in response to the following query: isopropyl alcohol -> gene -> biological process or activity -> cell -> anatomical entity -> nausea. Of note, users can interact with the graph and explore the supporting publications, which can be accessed by clicking on an edge. Users can also click on an edge to determine the provenance of predicate assertions between two nodes and associated metadata or click on a node to retrieve metadata, as shown here for “response to toxic substance”.
See this image and copyright information in PMC

References

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    1. 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. 10.1093/bioinformatics/btz604. - DOI - PMC - PubMed
    1. Biomedical Data Translator Consortium. Toward A Universal Biomedical Data Translator. Clin. Transl. Sci 2019, 12 (2), 86–90. - PMC - PubMed

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