# VIOLIN 2.0: Vaccine Information and Ontology LInked kNowledgebase

> **NIH NIH U24** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $740,422

## Abstract

Project Summary:
 Vaccination is one of the most successful innovations in the fight against infectious disease. However, we
still lack effective and safe vaccines against many major infectious diseases (e.g., HIV, tuberculosis, and
malaria). We also lack a comprehensive and interoperable vaccine knowledgebase to accelerate vaccine
development and better understand vaccine safety. Based on the preliminary version of our current VIOLIN
vaccine knowledgebase, we propose to develop VIOLIN 2.0, a new generation Vaccine Information and
Ontology LInked kNowledgebase.
Strong preliminary data were generated: Originally funded by an NIH-NIAID R01, our VIOLIN has grown
to include information on >4,000 vaccines for >200 pathogens. In addition, we have led the development of the
community-based Vaccine Ontology (VO) and Ontology of Adverse Events (OAE) for vaccine and adverse
event representation. We have also developed the widely used Vaxign and Vaxign-ML vaccine design
programs and applied them to predict vaccines for many diseases including COVID-19. Many ontology- and
bioinformatics-based methods and tools, including natural language processing (NLP) tools, have also been
developed to analyze vaccine information and identify new scientific insights. However, the existing VIOLIN
also faces new challenges in areas such as knowledge integration, interoperability, and analysis.
 In this proposal, we aim to systematically develop VIOLIN 2.0, which will be a community-based
comprehensive vaccine knowledgebase (KB) with data FAIRness. Basic science, clinical, and public health
(safety, epidemiology, vaccine coverage) knowledge will be included with robust linkage and analysis. Four
specific aims are proposed: Aim 1: Implement a pipeline for automatic knowledge harvest, standardization,
and integration using advanced ontology and natural language processing technologies. Aim 2: Expand the
vaccine KB and management. Three specific knowledge aspects will be included: (i) vaccine formulation and
development, (ii) protective responses, and (iii) vaccine safety. Aim 3: Provide VIOLIN 2.0 knowledge browser,
query, and showcases. For showcase demonstration, three use cases will be built up, including pattern
detection of vaccine components (including protective antigens and vaccine adjuvants), vaccine-induced host
immune signatures, and vaccine adverse events. The patterns identified will be utilized with statistical and
machine learning methods to support rational vaccine design and immune signature prediction. Aim 4:
Community engagement and outreach. Many events such as hackathons and workshops will be held to
support the development and applications of community-based ontologies, standards, and tools.
 VIOLIN 2.0 will significantly enhance the VIOLIN with breadth and depth of vaccine information, include
knowledge not available in the current VIOLIN (e.g., vaccine adverse events), and develop new methods for
efficient and scalable knowledge extraction and analysis....

## Key facts

- **NIH application ID:** 10854963
- **Project number:** 5U24AI171008-03
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Yongqun He
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $740,422
- **Award type:** 5
- **Project period:** 2022-08-19 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10854963

## Citation

> US National Institutes of Health, RePORTER application 10854963, VIOLIN 2.0: Vaccine Information and Ontology LInked kNowledgebase (5U24AI171008-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10854963. Licensed CC0.

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