Evidence map›Paper›PMID 37953304›Full record

ArticleNucleic acids research2024

The DO-KB Knowledgebase: a 20-year journey developing the disease open science ecosystem.

J Allen Baron, Claudia Sanchez-Beato Johnson, Michael A Schor, Dustin Olley, Lance Nickel, Victor Felix, James B Munro, Susan M Bello, Cynthia Bearer, Richard Lichenstein and 4 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
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

34 citing papers in PubMed.

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  14. Xenbase: A Guide to the Xenopus Genetics and Genomics Knowledgebase.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  15. Utilizing Large Language Models for Zero-Shot Medical Ontology Extension from Clinical Notes.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2025
    Article
  16. Article
  17. Article
  18. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

J Allen BaronUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
Claudia Sanchez-Beato JohnsonUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
Michael A SchorUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
Dustin OlleyUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.ORCID 0000-0001-8685-0839
Lance NickelUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
Victor FelixUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
James B MunroUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.ORCID 0000-0003-3067-6434
Susan M BelloMouse Genome Informatics, The Jackson Laboratory, Bar Harbor, ME, USA.ORCID 0000-0003-4606-0597
Cynthia BearerCase Western Reserve University, Cleveland, OH, USA.
Richard LichensteinUniversity of Maryland School of Medicine, Baltimore, MD, USA.
Katharine BisordiUniversity of Maryland School of Medicine, Baltimore, MD, USA.
Rima KokaUniversity of Maryland School of Medicine, Baltimore, MD, USA.
Carol GreeneUniversity of Maryland School of Medicine, Baltimore, MD, USA.
Lynn M SchrimlUniversity of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.ORCID 0000-0001-8910-9851

Funding

The Human Disease Ontology: An integrated, mechanistic knowledge resource for biomedical research.U24HG012557 · NHGRI · UNIVERSITY OF MARYLAND BALTIMORE · PI Lynn Marie Schriml · 2022 to 2026
$3.7M
The Disease Ontology Project: mechanistic profiles of human disease for biomedical and clinical researchU41HG008735 · NHGRI · UNIVERSITY OF MARYLAND BALTIMORE · PI SCHRIML, LYNN MARIE · 2017 to 2021
$3.4M
NHGRI NIH HHS 1U24HG012557-01NHGRI NIH HHS U24 HG012557NHGRI NIH HHS U41 HG008735NIH HHS U41 HG008735-01A1
6 · The paper itself

Abstract

In 2003, the Human Disease Ontology (DO, https://disease-ontology.org/) was established at Northwestern University. In the intervening 20 years, the DO has expanded to become a highly-utilized disease knowledge resource. Serving as the nomenclature and classification standard for human diseases, the DO provides a stable, etiology-based structure integrating mechanistic drivers of human disease. Over the past two decades the DO has grown from a collection of clinical vocabularies, into an expertly curated semantic resource of over 11300 common and rare diseases linking disease concepts through more than 37000 vocabulary cross mappings (v2023-08-08). Here, we introduce the recently launched DO Knowledgebase (DO-KB), which expands the DO's representation of the diseaseome and enhances the findability, accessibility, interoperability and reusability (FAIR) of disease data through a new SPARQL service and new Faceted Search Interface. The DO-KB is an integrated data system, built upon the DO's semantic disease knowledge backbone, with resources that expose and connect the DO's semantic knowledge with disease-related data across Open Linked Data resources. This update includes descriptions of efforts to assess the DO's global impact and improvements to data quality and content, with emphasis on changes in the last two years.

Indexed as

EcosystemKnowledge BasesHumansRare DiseasesSemanticsTime Factors

Identifiers

PMID37953304
PMCPMC10767934

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.