Evidence map›Paper›PMID 37131885›Full record

ArticleArXiv2023

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

Jackson Callaghan, Colleen H Xu, Jiwen Xin, Marco Alvarado Cano, Anders Riutta, Eric Zhou, Rohan Juneja, Yao Yao, Madhumita Narayan, Kristina Hanspers and 4 more

Open access · goldAbstract readPreprint
In one paragraph

Article in ArXiv, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 2 institutions in 1 country.

Jackson CallaghanDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Colleen H XuDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Jiwen XinDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Marco Alvarado CanoDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Anders RiuttaData Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, San Francisco, CA 94158, USA.
Eric ZhouDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Rohan JunejaDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Yao YaoDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Madhumita NarayanDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Kristina HanspersData Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, San Francisco, CA 94158, USA.
Ayushi AgrawalData Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, San Francisco, CA 94158, USA.
Alexander R PicoData Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, San Francisco, CA 94158, USA.
Chunlei WuDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Andrew I SuDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute.
Scripps Research Institute · USGladstone Institutes · US

Funding

BioThings Explorer: A platform for distributed knowledge integration across biomedical APIsOT2TR003427 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI SU, ANDREW I · 2020 to 2024
$5.2M
Expanding the landscape of Translator Knowledge Providers using BioThings SDK and SmartAPIOT2TR003445 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI WU, CHUNLEI · 2020 to 2024
$2.8M
NCATS NIH HHS OT2 TR003427NCATS NIH HHS OT2 TR003445
6 · The paper itself

Abstract

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, BioThing Explorer is distributed as a lightweight application that dynamically retrieves information at query time. More information can be found at https://explorer.biothings.io, and code is available at https://github.com/biothings/biothings_explorer.

Identifiers

PMID37131885
PMCPMC10153288
OpenAlexW4367835336

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.