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[Preprint]. 2025 Aug 15:2025.08.12.669998.
doi: 10.1101/2025.08.12.669998.

VO: The Vaccine Ontology

Affiliations

VO: The Vaccine Ontology

Jie Zheng et al. bioRxiv. .

Abstract

With the widespread use of vaccines in research and clinical settings, there is an urgent need to standardize vaccine representation, integrate information across diverse vaccine types, and support computer-assisted reasoning. Accordingly, we have since 2007 developed the community-based Vaccine Ontology (VO), which aligns with the Basic Formal Ontology and adheres to OBO Foundry principles. VO models ontologically vaccines, vaccine components, vaccine immune responses, vaccine investigation studies and other vaccine-related topics. VO represents more than 10,000 vaccines targeting 289 infectious pathogens and cancers in humans and over 30 nonhuman animal species. VO provides mappings to external resources such as RxNorm, CVX, FDA, and USDA. Various VO use cases exist. VO facilitates vaccine standardization in resources such as the VIOLIN vaccine database, ImmPort, and the Vaccine Adjuvant Compendium (VAC). Semantic queries can be made to query VO. VO has been shown to enhance experimental and clinical vaccine data analysis and vaccine literature mining. Overall, VO standardizes vaccine modeling and representation and greatly supports vaccine AI research in the Semantic Web era.

Keywords: FAIR; Semantic Web; VO; Vaccine Ontology; ontology; vaccination; vaccine.

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Conflict of interest statement

Competing Interests Dr. Yongqun He (Oliver) is an Editorial Board Member for Scientific Data, and has served as a Guest Editor for the “Data standards and ontologies for clinical and medical research” Collection.

Figures

Figure 1.
Figure 1.. High-level structure of VO.
(abridged: some intermediate non-VO terms omitted for simplicity)
Figure 2.
Figure 2.
Representative vaccine types and their associated hierarchies as defined in the VO.
Figure 3.
Figure 3.. VO representation of the LTA1 vaccine adjuvant.
(a) VO representation of the adjuvant, including three immune profiles induced by the adjuvant. (b) DL queries constructed from these three ‘immune profiles’ successfully retrieve the LTA1 adjuvant.
Figure 4.
Figure 4.. Vaccine ontology design pattern (ODP) in VO.
(a) ODP of a typical vaccine. (b) Illustration of vaccine ODP with ‘Afluria vaccine.’ (c) Representation of ‘Afluria vaccine’ in VO with inferred parents highlighted in yellow.
Figure 5.
Figure 5.. Semantic queries for vaccine identification based on vaccine features using DL and SPARQL query methods.
(a) Find Brucella vaccines; (b) Find influenza vaccines licensed for use in chickens; (c) Find vaccines that immunize against Bordetella pertussis defined in the OHDSI vocabularies with their IDs assigned by different resources
Figure 6.
Figure 6.. VO terms used in ImmPort.
(a) VO hierarchy of vaccines and adjuvants in ImmPort. (b) COVID-19 vaccine terms with number of studies in ImmPort. (c) Vaccine adjuvants with number of studies in ImmPort.

References

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    1. Centers for Disease Control and Prevention. CVX (Vaccine Administered), https://www2.cdc.gov/vaccines/iis/iisstandards/vaccines.asp?rpt=cvx (2024).
    1. U.S. Food and Drug Administration. FDA Approved Vaccines, https://www.fda.gov/vaccines-blood-biologics/vaccines/vaccines-licensed-... (2025).

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