CLAICEIRJan 20, 2025

Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications

Peking U
arXiv:2501.11632v214 citationsh-index: 13
Originality Synthesis-oriented
AI Analysis

It synthesizes existing BKG research for researchers and practitioners in biomedical fields, but it is incremental as a survey paper.

This survey addresses the lack of comprehensive reviews on biomedical knowledge graphs (BKGs) by systematically examining their domains, tasks, and real-world applications, providing a unified framework to clarify the current state and guide future research.

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.

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