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

本体支持的疫苗诱导途径和网络的综合分析和可视化

• 批准号: 9810625
• 负责人: Yongqun He
• 金额: $ 20.63万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-12 至 2021-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9810625
• 关键词: Address; Affect; Automobile Driving; Biological; Cells; Clinical Trials; Communicable Diseases; Communities; Community Developments; Data; Data Analyses; Data Set; Databases; Disease; Expression Profiling; Future; Gene Expression; Genes; Genetic; Health; Human; Imagery; Immune; Immune response; Immune system; Immunity; Immunologic Factors; Immunologics; Immunology; Influenza; Internet; Investigation; Manuals; Meta-Analysis; Metadata; Methods; Modeling; Modern Medicine; Molecular; Network-based; Online Systems; Ontology; Pathway interactions; Pattern; Peer Review; Process; Public Health; Publications; Research; Resources; Route; Semantics; Standardization; Statistical Data Interpretation; Statistical Methods; Testing; Vaccination; Vaccine Design; Vaccine Research; Vaccines; Visualization software; Work; Yellow Fever Vaccine; analysis pipeline; base; biomedical ontology; experimental study; human mortality; improved; insight; invention; knowledge base; pathogen; repository; response; secondary analysis; success; tool; user-friendly; vaccine development; vaccine trial; web app; web interface; web site

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.

项目概要： 尽管疫苗接种极大地保护了人类免受各种传染病的侵害，但仍然存在一些问题 许多致命疾病没有相应的疫苗。对于疫苗的合理开发至关重要 确定不同条件下针对传染性病原体的基本宿主免疫机制。 ImmPort 是世界上最大的免疫学相关临床试验数据公开存储库。这 对不同研究中的 ImmPort 疫苗研究数据进行二次分析，以确定疫苗引起的 在特定条件下的免疫效应器和相关途径将使我们更好地理解 疫苗与宿主相互作用的分子机制并支持合理的疫苗设计。 作为初步数据，我们开发了第一个基于网络的疫苗免疫效应数据库 VaximmutorDB 手动收集并注释了从同行鉴定的 1,700 多个疫苗免疫效应基因 审查出版物。我们还启动了基于社区的疫苗本体（VO）的开发 和疫苗调查本体（VIO），这将促进疫苗相关数据和元数据 标准化、集成和分析。此外，我们与其他团体一起开发了一条途径 名为Reactome的知识库，包含许多与传染病和宿主免疫相关的途径 Reactome 网站中使用的响应和路径可视化工具以及 Cytoscape 应用程序。 在这个项目中，我们的目标是进一步开发 VO 和 VIO，应用基于本体的集成方法 系统地表示、标准化、处理和分析来自以下来源的疫苗相关基因表达数据： 不同的实验研究，确定核心和差异疫苗诱导的免疫效应器、途径和 在特定实验条件下（例如疫苗类型、宿主细胞、疫苗接种途径）建立网络 基于本体的疫苗免疫效应知识库，并开发可视化工具，更好地查询和 对二次分析的疫苗免疫学数据进行分析。流感和黄热病疫苗研究 将被强调为驱动用例。将开发新的基于本体的统计方法 应用。除了从这项研究中获得的科学见解之外，由此产生的基于本体的工具和 方法将极大地支持免疫学数据标准化、表示、可视化和分析。