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: 10270593
• 负责人: PETER G DEUSTACHIO
• 金额: $ 85.92万
• 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/10270593
• 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; knowledge base; 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。反应- 托姆整合了关于描述人类的相互关联的生物途径的信息， 分子水平的生物学。拟议的工作将扩大政府间办事处与 Reactome项目，以更好地整合内容目前孤立在两个资源和几个 相关的参考资源，以提供一个更充分的互操作性开放获取资源， 生物医学研究社区。 GO提供了广泛使用的工具，用于将单个基因产物与细胞组分相关联， 它是其中的一部分，它所介导的分子功能，以及它所参与的生物过程。 参与。Reactome知识库中生物反应的注释集成 许多这样的原子GO断言涉及基因产物，因为它们在生物亲- cesses，对使用GO注释的研究人员具有巨大潜在价值的信息，但很难 使用，因为这两个是制定不同。最近开发的GO因果活动 模型（GO-CAM）形式主义，它扩展了原子GO注释，以捕获和集成en- 轮胎生物过程，可以形成GO和Reactome的路径之间的整合的基础- #21453;的方式，提高其实用性。 我们建议通过开发工具来开发一个集成的路径/本体资源，以有效地 及时提取GO-CAM模型内容，并进一步将GO-CAM / Reactome模型与 关键参考资源，如Rhea（专家策划的生化反应数据库） 蛋白质本体论（Protein Ontology，PRO）是蛋白质相关实体的本体论表示。 具体来说，我们将1）为每个Reactome途径生成GO-CAM模型， 2）协调Reactome和GO之间的策展和QA; 3)支持资源之间的数据交换并交叉验证映射;以及4）扩展此 致力于支持高效、部分自动化地创建模式生物的途径资源。 最终的结果将是一个开源的、集成的工具和数据集， 人类和模拟生物体的生物过程，支持各种数据挖掘，分析， 建模活动。这些工具和数据将被整合到GO、Reactome、PRO和 参与模式生物资源，支持关键社区的长期调整， 在这个项目完成后。