# Ontology-supported Integrative Analysis and Visualization of Vaccine-induced Pathways and Networks

> **NIH NIH UH2** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $231,114

## Abstract

Project Summary:
Although vaccination has dramatically protected humans against various infectious diseases, there are still
many deadly diseases that do not have corresponding vaccines. For rational vaccine development, it is crucial
to identify the fundamental host immune mechanisms against infectious pathogens under different conditions.
ImmPort is the world's largest repository for publicly de-identified clinical trial data related to immunology. The
secondary analysis of the ImmPort vaccine research data across different studies to identify vaccine-induced
immune effectors and related pathways given specific conditions would allow us to better understand
molecular mechanisms of vaccine-host interactions and support rational vaccine design.
As preliminary data, we have developed the first web-based vaccine immune effector database VaximmutorDB
that has manually collected and annotated over 1,700 vaccine immune effector genes identified from peer-
reviewed publications. We have also initiated the development of community-based Vaccine Ontology (VO)
and Vaccine Investigation Ontology (VIO), which will facilitate vaccine-related data and metadata
standardization, integration and analysis. In addition, together with other groups we have developed a pathway
knowledge base called Reactome, containing many pathways related to infectious diseases and host immune
responses, and pathway visualization tools that are being used in the Reactome website as well as a
Cytoscape app.
In this project, we aim to further develop the VO and VIO, apply ontology-based integrative approaches to
systematically represent, standardize, process, and analyze vaccine-related gene expression data from
different experimental studies, identify core and differential vaccine-induced immune effectors, pathways and
networks under specific experimental conditions (e.g., vaccine type, host cell, vaccination route), establish an
ontology-based vaccine immune effector knowledge base, and develop visualization tools to better query and
analyze the secondarily analyzed vaccine immunological data. The influenza and yellow fever vaccine studies
will be emphasized as driving use cases. New ontology-based statistical methods will be developed and
applied. In addition to the scientific insights obtained from this study, the resulting ontology-based tools and
methods will significantly support immunology data standardization, representation, visualization, and analysis.

## Key facts

- **NIH application ID:** 9952308
- **Project number:** 5UH2AI132931-02
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Yongqun He
- **Activity code:** UH2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $231,114
- **Award type:** 5
- **Project period:** 2019-06-12 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9952308

## Citation

> US National Institutes of Health, RePORTER application 9952308, Ontology-supported Integrative Analysis and Visualization of Vaccine-induced Pathways and Networks (5UH2AI132931-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9952308. Licensed CC0.

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