药物-基因相互作用数据库（DGIdb，https://dgidb.org）是一个可公开访问的资源，聚合基因或基因产物、药物和药物-基因相互作用记录，以推动临床医生和研究人员的假设生成和发现。 DGIdb 5.0 是最新版本，包括大量的架构和功能更新，以支持集成到临床和药物发现流程中。 DGIdb 服务架构已分为单独的客户端和服务器应用程序，从而为应用程序编程接口 (API) 和 Web 界面的用户提供一致的数据访问。新界面是用 ReactJS 开发的，包括动态可视化和用户界面元素显示的一致性。添加了 GraphQL API 以支持对所有药物、基因、注释和相关数据的可定制查询。更新的文档为用户提供了这些新功能的示例查询和详细使用说明。此外，还添加了六个源，并且更新了许多现有源。新添加的来源包括 ChemIDplus、HemOnc、NCIt（美国国家癌症研究所同义词库）、Drugs@FDA、HGNC（HUGO 基因命名委员会）和 RxNorm。这些新来源已被纳入 DGIdb，以提供额外的记录并增强治疗药物监管批准状态的注释。在导入过程中，药物和基因分组的方法已被扩展并开发为独立的模块化标准化器。这些来源和分组方法的更新改进了 DGIdb 中 FAIR（可查找性、可访问性、互操作性和可重用性）数据表示。© 作者 2023。由牛津大学出版社代表 Nucleic Acids Research 出版。

The Drug-Gene Interaction Database (DGIdb, https://dgidb.org) is a publicly accessible resource that aggregates genes or gene products, drugs and drug-gene interaction records to drive hypothesis generation and discovery for clinicians and researchers. DGIdb 5.0 is the latest release and includes substantial architectural and functional updates to support integration into clinical and drug discovery pipelines. The DGIdb service architecture has been split into separate client and server applications, enabling consistent data access for users of both the application programming interface (API) and web interface. The new interface was developed in ReactJS, and includes dynamic visualizations and consistency in the display of user interface elements. A GraphQL API has been added to support customizable queries for all drugs, genes, annotations and associated data. Updated documentation provides users with example queries and detailed usage instructions for these new features. In addition, six sources have been added and many existing sources have been updated. Newly added sources include ChemIDplus, HemOnc, NCIt (National Cancer Institute Thesaurus), Drugs@FDA, HGNC (HUGO Gene Nomenclature Committee) and RxNorm. These new sources have been incorporated into DGIdb to provide additional records and enhance annotations of regulatory approval status for therapeutics. Methods for grouping drugs and genes have been expanded upon and developed as independent modular normalizers during import. The updates to these sources and grouping methods have resulted in an improvement in FAIR (findability, accessibility, interoperability and reusability) data representation in DGIdb.© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.