可互操作的生物医学本体在系统医学中的综合数据和知识表示以及多尺度建模中的开发与应用。

Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems Medicine.

机构信息

Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.

出版信息

Methods Mol Biol. 2022;2486:233-244. doi: 10.1007/978-1-0716-2265-0_12.

DOI:10.1007/978-1-0716-2265-0_12

PMID:35437726

Abstract

The data FAIR Guiding Principles state that all data should be Findable, Accessible, Interoperable, and Reusable. Ontology is critical to data integration, sharing, and analysis. Given thousands of ontologies have been developed in the era of artificial intelligence, it is critical to have interoperable ontologies to support standardized data and knowledge presentation and reasoning. For interoperable ontology development, the eXtensible ontology development (XOD) strategy offers four principles including ontology term reuse, semantic alignment, ontology design pattern usage, and community extensibility. Many software programs are available to help implement these principles. As a demonstration, the XOD strategy is applied to developing the interoperable Coronavirus Infectious Disease Ontology (CIDO). Various applications of interoperable ontologies, such as COVID-19 and kidney precision medicine research, are also introduced in this chapter.

摘要

数据 FAIR 指导原则指出，所有数据都应该是可发现、可访问、可互操作和可重复使用的。本体对于数据集成、共享和分析至关重要。考虑到在人工智能时代已经开发了数千个本体，拥有可互操作的本体对于支持标准化的数据和知识表示和推理至关重要。对于可互操作的本体开发，可扩展本体开发 (XOD) 策略提供了包括本体术语重用、语义对齐、本体设计模式使用和社区可扩展性在内的四项原则。有许多软件程序可用于帮助实施这些原则。作为一个演示，XOD 策略被应用于开发可互操作的冠状病毒传染病本体 (CIDO)。本章还介绍了可互操作本体的各种应用，如 COVID-19 和肾脏精准医学研究。