Ontology-based Information Network to Support Vaccine Research

基于本体的信息网络支持疫苗研究

• 批准号: 7935464
• 负责人: Yongqun He
• 金额: $ 26.77万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-22 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7935464
• 关键词: Algorithms; Attenuated Live Virus Vaccine; Automated Annotation; Bacterial Genes; Brucella; Brucella Vaccine; Clinical Trials; Collaborations; Communicable Diseases; Communities; Consensus; Controlled Vocabulary; Data; Databases; Development; Dictionary; Ensure; Escherichia coli; Escherichia coli Vaccines; Foundations; Genome; Genomics; Goals; Immune; Immune response; Immune system; Immunity; Informatics; Information Networks; Information Retrieval; Journals; Laboratories; Literature; MeSH Thesaurus; Methodology; Methods; Modeling; National Center for Integrative Biomedical Informatics; Natural Language Processing; Online Systems; Ontology; Organism; Paper; Preparation; Process; Proteins; Publications; Publishing; Research; Research Personnel; Retrieval; Scientist; Smallpox Vaccine; Staging; Standardization; Structure; Subunit Vaccines; System; Testing; Training; Vaccine Research; Vaccines; base; biomedical ontology; computer based Semantic Analysis; data integration; editorial; gene function; genome-wide; interest; journal article; knowledge base; microorganism; novel; novel vaccines; pathogen; programs; repository; research study; statistics; text searching; user-friendly; vaccine candidate; vaccine development; vaccine evaluation; web interface

DESCRIPTION (provided by applicant): Since the introduction of Edward Jenner's smallpox vaccine in 1796, vaccines have proven invaluable for their ability to stimulate the immune system and to confer protection against pathogenic organisms. Progress in modern vaccine research has been accompanied by a dramatic increase in the number of vaccine-related papers in the published literature. It has become increasingly challenging to identify and annotate vaccine data from this large and diverse literature which no one scientist or team can fully master. Although vaccine databases exist that emphasize commercialized vaccines, no public central repository is available to store research data concerning commercial vaccines, vaccines in clinical trials, or vaccine candidates in early stages of development, in a fashion that render such data available for advanced analyses. To fill this need, we have developed VIOLIN (http://www.violinet.org), a web-based database system for annotation, storage, and analysis of published vaccine data. An ontology represents consensus-based controlled vocabularies of terms and relations, with associated definitions which are logically formulated in such a way as to promote automated reasoning. A bottleneck of vaccine research and further VIOLIN development is the lack of a vaccine ontology, which in turn makes a significant obstacle for vaccine data standardization, retrieval, integration, and advanced analysis and prediction. Our goal is to develop the community-based Vaccine Ontology (VO) and apply it to efficient vaccine literature mining and analysis of protective immune mechanisms. We will focus on two model pathogens: Escherichia coli and Brucella species. This project contains three specific aims: (1) develop a community-based Vaccine Ontology (VO), and apply it to establish a vaccine knowledgebase and to promote vaccine data integration and query through Semantic Web. The VO development will be achieved through collaboration with vaccine researchers, the Infectious Disease Ontology (IDO) Initiative, and the National Center for Biomedical Ontology (NCBO); (2) develop a VO-based natural language processing (NLP) system and apply it for more efficient retrieval of Brucella and E. coli vaccine information, automated annotation of journal articles with VO terms, and VO improvement. This task will be achieved by collaboration with the National Center for Integrative Biomedical Informatics (NCIBI). (3) analyze and predict vaccine targets and protective immune networks attributable to the interactions between host and vaccine. This will be achieved mainly by VO-based literature mining and a novel genome- and literature-based statistical methodology. This project will be implemented by a strong collaborative team and supported from a large user community. The Vaccine Ontology and its applications to literature mining and for studying protective immunity against Brucella spp. and E. coli will lay a strong foundation for further advanced informatics research on vaccines against infectious diseases in the post-genomics and information era.

描述（由申请方提供）：自1796年爱德华詹纳的天花疫苗问世以来，疫苗已被证明具有刺激免疫系统和保护机体免受病原体侵害的宝贵能力。现代疫苗研究的进展伴随着出版文献中与疫苗相关的论文数量的急剧增加。从这些庞大而多样的文献中识别和注释疫苗数据变得越来越具有挑战性，没有一个科学家或团队可以完全掌握这些文献。虽然存在强调商业化疫苗的疫苗数据库，但没有公共中央储存库可用于存储有关商业疫苗、临床试验中的疫苗或处于早期开发阶段的候选疫苗的研究数据，从而使这些数据可用于高级分析。为了满足这一需求，我们开发了VIOLIN（http：www.violinet.org），这是一个基于网络的数据库系统，用于注释、存储和分析已发表的疫苗数据。本体表示基于共识的术语和关系的受控词汇表，以及以促进自动推理的方式逻辑地制定的相关定义。疫苗研究和VIOLIN进一步发展的瓶颈是缺乏疫苗本体，这反过来又成为疫苗数据标准化，检索，集成以及高级分析和预测的重大障碍。我们的目标是开发基于社区的疫苗本体（VO），并将其应用于有效的疫苗文献挖掘和保护性免疫机制的分析。我们将集中在两个模式病原体：大肠杆菌和布鲁氏菌物种。本项目的具体目标有三个：（1）开发基于社区的疫苗本体，并将其应用于疫苗知识库的建立，以及通过语义网实现疫苗数据的集成和查询。VO的开发将通过与疫苗研究人员、传染病本体论（IDO）倡议和国家生物医学本体论中心（NCBO）的合作来实现;（2）开发基于VO的自然语言处理（NLP）系统，并将其应用于更有效的布鲁氏菌和E.大肠杆菌疫苗信息，自动标注的期刊文章与VO术语，VO的改进。这项任务将通过与国家综合生物医学信息学中心（NCIBI）合作来实现。(3)分析和预测疫苗靶点和宿主与疫苗相互作用产生的保护性免疫网络。这将主要通过基于VO的文献挖掘和一种新的基于基因组和文献的统计方法来实现。该项目将由强大的协作团队实施，并得到大型用户社区的支持。疫苗本体及其在文献挖掘和布鲁氏菌保护性免疫研究中的应用。和E.大肠杆菌的研究将为后基因组学和信息时代传染病疫苗的进一步信息学研究奠定坚实的基础。