Evidence map›Paper›PMID 38883236›Full record

ArticleArXiv2025

The Vertebrate Breed Ontology: Towards effective breed data standardization.

Kathleen R Mullen, Imke Tammen, Nicolas A Matentzoglu, Marius Mather, James P Balhoff, Elizabeth Esdaile, Gregoire Leroy, Carissa A Park, Halie M Rando, Nadia T Saklou and 6 more

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2025. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Kathleen R MullenDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Imke TammenSydney School of Veterinary Science, The University of Sydney, Sydney, NSW, Australia.
Nicolas A MatentzogluSemanticly Ltd, Athens, Greece.
Marius MatherSydney Informatics Hub, The University of Sydney, Sydney, NSW, Australia.
James P BalhoffRenaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Elizabeth EsdaileVeterinary Genetics Laboratory, School of Veterinary Medicine, University of California, Davis, CA, USA. Current affiliation is Department of Clinical Sciences, Colorado State University, Fort Collins, CO, USA.
Gregoire LeroyAnimal Production and Health Division, Food and Agriculture Organization of the United Nations, Rome, Italy.
Carissa A ParkDepartment of Animal Science, Iowa State University, Ames, IA, USA.
Halie M RandoDepartment of Computer Science, Smith College, Northampton, MA, USA.
Nadia T SaklouDepartment of Clinical Sciences, Colorado State University, Fort Collins, CO, USA.
Tracy L WebbDepartment of Clinical Sciences, Colorado State University, Fort Collins, CO, USA.
Nicole A VasilevskyData Collaboration Center, Critical Path Institute, Tucson, AZ, USA.
Christopher J MungallLawrence Berkeley National Laboratory, Berkeley, CA, USA.
Melissa A HaendelDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Frank W NicholasSydney School of Veterinary Science, The University of Sydney, Sydney, NSW, Australia.
Sabrina ToroDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Funding

Colorado Clinical and Translational Sciences Institute (CCTSI)UM1TR004399 · NCATS · UNIVERSITY OF COLORADO DENVER · PI JANINE A HIGGINS, RONALD J. SOKOL · 2023 to 2026
$30.7M
The Monarch Initiative: Linking Diseases to Model Organism ResourcesR24OD011883 · OD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HAENDEL, MELISSA A, MUNGALL, CHRISTOPHER J · 2012 to 2024
$16.0M
Translational Research Workforce Training: Leveraging the Veterinary SpecialistU01TR002953 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI TREPANIER, LAUREN A · 2019 to 2024
$2.6M
The Colorado Building Interdisciplinary Research Careers in Women's Health ProgramK12AR084226 · NIAMS · UNIVERSITY OF COLORADO DENVER · PI JUDITH G. REGENSTEINER, Nanette F. Santoro · 2023 to 2026
$2.5M
NCATS NIH HHS U01 TR002953NCATS NIH HHS UM1 TR004399NIAMS NIH HHS K12 AR084226NIH HHS R24 OD011883
6 · The paper itself

Abstract

Background –: Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information-based tools to support advancement in diagnostics, treatments, and precision medicine. Hypothesis/Objectives –: A single, coherent, logic-based standard for documenting breed names in health, production, and research-related records will improve data use capabilities in veterinary and comparative medicine. Animals –: No live animals were used. Methods –: The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence-readiness. Results –: VBO is an open, community-driven ontology representing over 19,500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross-references to other databases. Conclusion and clinical importance –: The adoption of VBO as a source of standard breed names in databases and veterinary electronic health records can enhance veterinary data interoperability and computability.

Indexed as

animal population groupsbiological ontologiesbreedinggeneticsprecision medicine

Identifiers

PMID38883236
PMCPMC11177956

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.