BIOLOGICAL KNOWLEDGE-BASED MANAGEMENT SYSTEM

基于生物知识的管理系统

• 批准号: 3474540
• 负责人: PETER D KARP
• 金额: $ 14.8万
• 依托单位: SRI INTERNATIONAL
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-01-01 至 1997-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3474540
• 关键词: artificial intelligence; computer program /software; enzyme activity; information system analysis; information systems; metabolism

Biomedical researchers are generating vast amounts of data and knowledge, at an accelerating pace. Neither existing database systems nor existing frame knowledge representation systems have the capabilities required to support the development of large, shared repositories of biological information. Therefore, SRI International proposes to integrate database and knowledge-representation technology to develop a biological knowledge-base management system (KBMS) with unprecedented power to en- code biological knowledge. This KBMS will provide the expressive power needed to represent biological knowledge in all its complexity, will support the evolution of complex knowledge-base schemas, will enable multiple users to access large amounts of reliably stored information in a shared fashion, and will support inference over this knowledge. Our implementation efforts will build on an existing frame representation system called THEO. We will extend THEO so that its underlying storage system utilizes a database management system to facilitate the construction of frame knowledge bases containing large numbers (millions) of persistent frames. In addition, we will implement a collaboration subsystem that coordinates concurrent distributed development of large knowledge bases by multiple users. To exercise and validate our development efforts, this KBMS will be used in an application to construct a large biological knowledge base of intermediary metabolism.

生物医学研究人员正在产生大量的数据和知识， 以加速的步伐。 既没有现有的数据库系统， 框架知识表示系统具有所需的能力， 支持开发大型共享的生物资源库， 信息. 因此，SRI国际建议将数据库 和知识表达技术来开发一个生物 知识库管理系统（KBMS）具有前所未有的力量， 密码生物学知识 该KBMS将提供表现力， 需要代表生物知识的所有复杂性，将 支持复杂知识库模式的演变，将使 多个用户访问大量可靠存储的信息， 一个共享的方式，并将支持对这一知识的推理。 我们的实现工作将建立在现有的框架表示 这个系统叫做THEO。 我们将扩展THEO， 系统利用数据库管理系统来促进 构建包含大量（百万）的框架知识库 持久帧。 此外，我们还将实施一项合作计划， 一个子系统，用于协调大型 多个用户的知识库。 为了练习和验证我们的开发工作， 在构建大型生物学知识库的应用中， 中间代谢