Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Sep 2;39(9):btad570.
doi: 10.1093/bioinformatics/btad570.

BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs

Affiliations

BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs

Jackson Callaghan et al. Bioinformatics. .

Abstract

Summary: Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist for querying and analyzing graphs. Biomedical knowledge graphs have been used in a variety of applications, including drug repurposing, identification of drug targets, prediction of drug side effects, and clinical decision support. Typically, knowledge graphs are constructed by centralization and integration of data from multiple disparate sources. Here, we describe BioThings Explorer, an application that can query a virtual, federated knowledge graph derived from the aggregated information in a network of biomedical web services. BioThings Explorer leverages semantically precise annotations of the inputs and outputs for each resource, and automates the chaining of web service calls to execute multi-step graph queries. Because there is no large, centralized knowledge graph to maintain, BioThings Explorer is distributed as a lightweight application that dynamically retrieves information at query time.

Availability and implementation: More information can be found at https://explorer.biothings.io and code is available at https://github.com/biothings/biothings_explorer.

PubMed Disclaimer

Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
A visualization of the meta-KG for BioThings Explorer. The nodes in this graph are the semantic types of biomedical entities that BioThings Explorer can retrieve associations between (limited to the top eight most common semantic types). The edges between nodes show what associations between biomedical entities exist in the semantic API network that is accessible through BioThings Explorer. The edge label shows the number of APIs that can retrieve those types of associations, which is also represented by the edge width.
Figure 2.
Figure 2.
Deconstruction of a query in BioThings Explorer. (A) A free-text representation of a query that can be answered by BioThings Explorer. (B) The graph representation of the same query. The exact syntax of this graph query is specified in the Translator Reasoner API standard described in Fecho et al. (2022) and shown in Supplementary Fig. S2. (C) The deconstruction of the graph query into multiple API calls by consulting the meta-KG in the SmartAPI registry.

Update of

References

    1. Cilibrasi RL, Vitanyi PMB. The google similarity distance. IEEE Trans Knowl Data Eng 2007;19:370–83.
    1. Davis AP, Wiegers TC, Johnson RJ et al. Comparative toxicogenomics database (CTD): update 2023. Nucleic Acids Res 2023;51:D1257–62. - PMC - PubMed
    1. Dowell RD, Jokerst RM, Day A et al. The distributed annotation system. BMC Bioinformatics 2001;2:7. - PMC - PubMed
    1. Fecho K, Bizon C, Miller F et al. A biomedical knowledge graph system to propose mechanistic hypotheses for real-world environmental health observations: cohort study and informatics application. JMIR Med Inform 2021;9:e26714. - PMC - PubMed
    1. Fecho K, Thessen AE, Baranzini SE et al. Progress toward a universal biomedical data translator. Clin Transl Sci 2022;15:1838–47. - PMC - PubMed

MeSH terms