Scholarlink

<p>Vaccines are widely used in both research and clinical settings. To facilitate FAIR data practices, we urgently 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 ontologically models 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. VO facilitates vaccine standardization in resources such as the VIOLIN vaccine database, ImmPort, and the Vaccine Adjuvant Compendium (VAC). VO enables semantic queries on vaccine data. It has been shown to enhance the analysis of experimental and clinical vaccine datasets, as well as vaccine-related literature mining. Overall, VO standardizes vaccine modeling and representation and greatly supports vaccine AI research in the Semantic Web era.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

VO: The Vaccine Ontology

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月30日

查看全文
  • Jie Zheng,
  • Asiyah Yu Lin,
  • Anthony Huffman,
  • Anna Maria Masci,
  • Rebecca Racz,
  • Guanming Wu,
  • Kallan Roan,
  • Edison Ong,
  • Sirarat Sarntivijai,
  • Joy Hu,
  • Eliyas Asfaw,
  • Hayleigh Kahn,
  • Xingxian Li,
  • Xumeng Zhang,
  • Joshua Monickaraj,
  • Nilufer Kosar,
  • Jianfu Li,
  • Warren Manuel,
  • Rashmie Abeysinghe,
  • Hasin Rehana,
  • Benu Bansal,
  • Yuanyi Pan,
  • Jinjing Guo,
  • Virginia He,
  • Justin Song,
  • Andrey I. Seleznev,
  • Katelyn Hur,
  • Anna He,
  • Alexander Davydov,
  • Qi Yang,
  • Anna Ostropolets,
  • Randi Vita,
  • Bjoern Peters,
  • Alan Ruttenberg,
  • Alexander D. Diehl,
  • Charles Tapley Hoyt,
  • Paola Roncaglia,
  • Rachael P. Huntley,
  • Richard H. Scheuermann,
  • Melanie Courtot,
  • Thomas Todd,
  • Samantha Sayers,
  • Fang Chen,
  • Xinna Li,
  • Feng-Yu Yeh,
  • Zuoshuang Xiang,
  • Arzucan Ozgur,
  • Patricia L. Whetzel,
  • Mark A. Musen,
  • Christopher J. Mungall,
  • Wolfgang W. Leitner,
  • Licong Cui,
  • Lesley A. Colby,
  • Harry L. T. Mobley,
  • Brian D. Athey,
  • Gilbert S. Omenn,
  • Lindsay G. Cowell,
  • Cui Tao,
  • Junguk Hur,
  • Barry Smith,
  • Yongqun He

摘要

Vaccines are widely used in both research and clinical settings. To facilitate FAIR data practices, we urgently 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 ontologically models 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. VO facilitates vaccine standardization in resources such as the VIOLIN vaccine database, ImmPort, and the Vaccine Adjuvant Compendium (VAC). VO enables semantic queries on vaccine data. It has been shown to enhance the analysis of experimental and clinical vaccine datasets, as well as vaccine-related literature mining. Overall, VO standardizes vaccine modeling and representation and greatly supports vaccine AI research in the Semantic Web era.