[论文解读] Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications

Yuxing Lu, Sin Yee Goi+2 more|ArXiv.org|Jan 20, 2025

Biomedical Text Mining and Ontologies被引用 4

一句话总结

本综述通过考察 Biomedical Knowledge Graphs (BKGs) 的领域覆盖、核心任务与在精准医疗、药物发现和科学研究中的现实世界应用，提供一个统一框架。

ABSTRACT

Biomedical knowledge graphs (BKGs) have emerged as powerful tools for organizing and leveraging the vast and complex data found across the biomedical field. Yet, current reviews of BKGs often limit their scope to specific domains or methods, overlooking the broader landscape and the rapid technological progress reshaping it. In this survey, we address this gap by offering a systematic review of BKGs from three core perspectives: domains, tasks, and applications. We begin by examining how BKGs are constructed from diverse data sources, including molecular interactions, pharmacological datasets, and clinical records. Next, we discuss the essential tasks enabled by BKGs, focusing on knowledge management, retrieval, reasoning, and interpretation. Finally, we highlight real-world applications in precision medicine, drug discovery, and scientific research, illustrating the translational impact of BKGs across multiple sectors. By synthesizing these perspectives into a unified framework, this survey not only clarifies the current state of BKG research but also establishes a foundation for future exploration, enabling both innovative methodological advances and practical implementations.

研究动机与目标

• 澄清 BKGs 如何从分子相互作用、药理数据集和临床记录等多样数据来源构建。
• 确定 BKGs 支持的核心任务，包括知识管理、检索、推理与解读。
• 突出 BKGs 在精准医疗、药物发现与科学研究中的现实世界转化应用。

提出的方法

• 对跨域、跨任务和跨应用的 BKGs 进行系统综述。
• 汇总为统一框架，以澄清现状并指引未来工作。
• 讨论构建 BKGs 的数据来源与集成策略。

实验结果

研究问题

• RQ1 Biomedical Knowledge Graphs 覆盖哪些领域，如何从多样数据来源构建？
• RQ2 BKGs 支持的核心任务（知识管理、检索、推理、解读）是什么，如何实现？
• RQ3 哪些现实世界应用体现 BKGs 在医学和科学中的转化影响？

主要发现

• BKGs 汇聚来自分子相互作用、药理数据集和临床记录的数据。
• BKGs 支持知识管理、检索、推理和解读等任务。
• 突出显示的现实世界应用包括精准医疗、药物发现和科学研究。