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。蛋白质本体论（PRO）-OBO（开放生物和生物医学本体论）Foundry中蛋白质实体的参考本体论-代表蛋白质家族，由单个基因产生的多种蛋白质形式（蛋白质形式）和蛋白质复合物。这一竞争性的续期拨款申请将进一步建立PRO作为一个可扩展的，灵活的，协作的研究基础设施，以蛋白质为中心的语义集成的生物医学数据的数量和复杂性不断增加。具体目标是：（i）实现蛋白质类型的可扩展和动态表示;（ii）在其生物学背景下提供人类蛋白质的全面覆盖;（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。我们将通过半自动导入来自策展数据库的蛋白质和复合物以及通过已建立的文本挖掘方法来增加PRO覆盖率。专家策展将集中在人类变异形式，翻译后修饰（PTM）形式和复杂的疾病过程中至关重要，沿着同源小鼠形式。我们将开发一个新的PRO子本体的蛋白质位点的氨基酸位置的意义，使自动和动态定义的组合proteoforms。我们将建立PRO OWL和RDF版本，并提供一个SPARQL查询端点来支持语义计算。我们将组织年度研讨会和注释大会，以开发用例，并促进PRO与社区合作者的共同开发，以满足特定的学科需求。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水平上进行准确的注释，并提供了本体框架来连接PTM和变体蛋白质型以及模拟人类健康和疾病所需的复合物。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大量的蛋白质组学数据和生物医学知识，以支持假设生成和测试。因此，PRO解决了蛋白质表示的生物信息学基础设施的差距，使有关蛋白质的知识更容易获得计算推理，充分补充现有的知识来源。拟议的研究将使PRO联盟能够深化和扩大PRO，以实现生物医学数据的可扩展语义集成，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.