Reactome and the Gene Ontology: Digital pathway convergence for core data resources

Reactome 和基因本体：核心数据资源的数字路径融合

• 批准号: 10494099
• 负责人: PETER G DEUSTACHIO
• 金额: $ 68.36万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10494099
• 关键词: Animal Model; Automated Annotation; Automation; Biochemical Reaction; Bioinformatics; Biological; Biological Models; Biological Process; Biomedical Research; Caenorhabditis elegans; Chemicals; Chemistry; Collaborations; Communicable Diseases; Communities; Complex; Computer Analysis; Coupled; Data; Databases; Development; Ensure; Foundations; Funding; Generations; Genes; Goals; Human; Human Biology; Individual; Laboratory mice; Life; Mediating; Modeling; Molecular; National Human Genome Research Institute; Nematoda; Ontology; Pathway interactions; Planet Earth; Procedures; Process; Protein Family; Proteins; Reaction; Research Personnel; Resources; Rhea; Seeds; Source; System; Translating; Validation; Work; base; biomedical resource; data exchange; data mining; data resource; data standards; digital; diverse data; gene function; gene product; interoperability; knowledgebase; man; open source; protein complex; prototype; tool

The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes, and is a foundation for computational analysis in biomedical research. Reac- tome integrates information about the interconnected biological pathways that describe human biology at a molecular level. The proposed work will extend a collaboration between the GO and Reactome projects to better integrate content currently siloed in the two resources and several related reference resources to provide a more fully interoperable open access resource for the biomedical research community. GO provides widely-used tools for associating an individual gene product with a cellular compo- nent of which it is a part, a molecular function it mediates, and a biological process in which it participates. Annotations of biological reactions in the Reactome Knowledgebase integrate many such atomic GO assertions concerning gene products as they interact in biological pro- cesses, information of great potential value to researchers who use GO annotations, but hard to use because the two are formulated differently. The recently developed GO Causal Activity Model (GO-CAM) formalism, which extends atomic GO annotation to capture and integrate en- tire biological processes, can form the basis of integration between GO and Reactome's path- way models, increasing their utility. We propose to develop an integrated pathway/ontology resource by developing tools to effi- ciently extract GO-CAM model content and further integrate GO-CAM / Reactome models with key reference resources such as Rhea (a database of expert-curated biochemical reactions) and the Protein Ontology (PRO), an ontological representation of protein-related entities. Specifically, we will 1) generate GO-CAM models for every Reactome pathway that represents a normal human biological process; 2) coordinate curation and QA between Reactome and GO; 3) support data exchange among resources and cross-validate the mappings; and 4) extend this work to support efficient, partly automated creation of pathway resources for model organisms. The end result will be an open-source, integrated set of tools and data that accurately represent human and model organism biological processes, supporting diverse data mining, analysis, and modeling activities. These tools and data will be incorporated into GO, Reactome, PRO, and participating model organism resources, supporting long-term alignment of key community re- sources after the completion of this project.

基因本体论（GO）知识库是世界上最大的信息来源 基因的功能，是生物医学研究中计算分析的基础。重新 Tome整合了描述人类的相互联系的生物学途径的信息 分子水平的生物学。拟议的工作将扩大行动之间的合作 Reactome项目目前在两个资源中孤立的更好的集成内容，有几个 相关的参考资源为提供更完全互操作的开放访问资源 生物医学研究界。 GO提供了广泛使用的工具，可以将单个基因产品与细胞组合相关联 它是其中的一部分，它介导的分子函数和它的生物学过程 参加。 Reactome Knowledgebase中生物反应的注释集成 许多关于基因产物在生物学方面相互作用的基因产物的主张 Cesses，对于使用GO注释但难以实现的研究人员的潜在价值的信息，但很难 使用是因为两者的配制方式不同。最近开发的GO因果活动 模型（GO-CAM）格式，该格式扩展了原子GO注释以捕获和整合en- 轮胎生物过程，可以构成GO和Reactome路径之间整合的基础 - 方式模型，增加了效用。 我们建议通过开发努力工具来开发综合途径/本体学资源 - 将GO-CAM模型内容提取，并与 关键参考资源，例如RHEA（专家策划的生化反应数据库） 以及蛋白质本体论（PRO），这是蛋白质相关实体的本体论表示。 具体而言，我们将为每一个代表的每个反应组途径生成go-cam模型 正常的人类生物学过程； 2）在Reactome和GO之间进行协调策划和QA； 3）支持资源之间的数据交换并跨质量映射； 4）扩展此 努力支持为模型生物的高效，部分自动创建途径资源。 最终结果将是一组开源的集成的工具和数据集，可以准确表示 人类和模型有机体生物学过程，支持潜水员数据挖掘，分析和 建模活动。这些工具和数据将纳入GO，Reactome，Pro和 参与模型的有机体资源，支持关键社区的长期一致性 该项目完成后的来源。