PRO: A Protein Ontology in OBO Foundry for Scalable Integration of Biomedical Knowledge

 描述(由申请人提供)：项目摘要生物医学本体论对于生物医学和临床研究中基因组规模数据的准确表示和整合至关重要。蛋白质本体(PRO)-OBO(开放式生物和生物医学本体)铸造中蛋白质实体的参考本体-代表蛋白质家族、由单基因产生的多种蛋白质形式(蛋白质形式)和蛋白质复合体。这一竞争性续签拨款申请将进一步将PRO确立为可扩展、灵活、协作的研究基础设施，用于数量和复杂性不断增加的以蛋白质为中心的生物医学数据的语义集成。具体目标是：(I)实现蛋白质类型的可伸缩和动态表示；(Ii)在其生物学背景下提供对人类蛋白质形式的全面覆盖；(Iii)开发协作用例并支持不断扩大的用户社区以促进对蛋白质疾病的理解；以及(Iv)扩大传播以支持语义计算、动态术语映射以及互操作性和可重用性。我们将通过半自动地从精选数据库中导入蛋白质形式和复合体以及通过已建立的文本挖掘方法来扩大PRO的覆盖面。专家策展将重点关注人类变异形式、翻译后修饰(PTM)形式和对疾病过程至关重要的复合体，以及同源小鼠形式。我们将开发一个新的蛋白质位置的PRO子本体-重要的氨基酸位置-以实现组合蛋白质形式的自动和动态定义。我们将建立PRO OWL和RDF版本，并提供SPARQL查询端点来支持语义计算。我们将举办年度工作坊和注释研讨会，以开发使用案例，并促进与社区合作者的专业合作开发，以满足特定的纪律需求。Pro有几个独特的功能。对于知识表示，PRO定义了精确的蛋白质实体，以支持在适当的粒度级别进行准确的注释，并提供了本体框架来连接PTM和对人类健康和疾病建模所需的各种蛋白质形式和复合体。对于语义数据集成，PRO提供了本体结构，通过指定的关系连接海量的蛋白质组数据和生物医学知识，以支持假设的生成和测试。因此，PRO解决了蛋白质表示的生物信息学基础设施中的空白，使有关蛋白质的知识更易于计算推理，完全补充了现有的知识来源。拟议的研究将使PRO联盟能够深化和扩大PRO，以便对生物医学数据进行可扩展的语义集成，通过不断扩大的生物医学、临床和计算用户社区促进蛋白质疾病知识的发现和临床应用。

 DESCRIPTION (provided by applicant): PROJECT SUMMARY Biomedical ontologies are critical to the accurate representation and integration of genome-scale data in biomedical and clinical research. The Protein Ontology (PRO)-the reference ontology for protein entities in the OBO (Open Biological and Biomedical Ontologies) Foundry-represents protein families, multiple protein forms (proteoforms) arising from single genes, and protein complexes. This competitive renewal grant application will further establish PRO as a scalable, flexible, collaborative research infrastructure for protein-centric semantic integration of biomedical data of increasing volume and complexity. Specific aims are to: (i) enable scalable and dynamic representation of protein types; (ii) provide comprehensive coverage of human proteoforms in their biological context; (iii) develop collaborative use cases and support an expanding community of users to advance protein-disease understanding; and (iv) broaden dissemination to support semantic computing, dynamic term mapping, and interoperability and reusability. We will increase PRO coverage by semi-automated import of proteoforms and complexes from curated databases and via established text mining approaches. Expert curation will focus on human variant forms, post-translational modification (PTM) forms and complexes critical to disease processes, along with homologous mouse forms. We will develop a new PRO sub-ontology of protein sites-amino acid positions of significance-to enable automatic and dynamic definition of combinatoric proteoforms. We will establish PRO OWL and RDF versions and provide a SPARQL query endpoint to support semantic computing. We will organize annual workshops and annotation jamborees to develop use cases and promote PRO co-development with community collaborators to address specific disciplinary needs. PRO has several unique features. For knowledge representation, PRO defines precise protein entities to support accurate annotation at the appropriate level of granularity and provides the ontological framework to connect PTM and variant proteoforms and complexes necessary to model human health and disease. For semantic data integration, PRO provides the ontological structure to connect-via specified relations-the vast amounts of proteomics data and biomedical knowledge to support hypothesis generation and testing. PRO therefore addresses the gaps in the bioinformatics infrastructure for protein representations in a way that makes knowledge about proteins more accessible to computational reasoning, fully complementing existing knowledge sources. The proposed research will allow the PRO Consortium to deepen and broaden PRO for scalable semantic integration of biomedical data, facilitating protein-disease knowledge discovery and clinical applications by an expanding community of biomedical, clinical and computational users.