The abundance of biomedical knowledge gained from biological experiments and clinical practices is an invaluable resource for biomedicine. The emerging biomedical knowledge graphs (BKGs) provide an efficient and effective way to manage the abundant knowledge in biomedical and life science. In this study, we created a comprehensive BKG called the integrative Biomedical Knowledge Hub (iBKH) by harmonizing and integrating information from diverse biomedical resources. To make iBKH easily accessible for biomedical research, we developed a web-based, user-friendly graphical portal that allows fast and interactive knowledge retrieval. Additionally, we also implemented an efficient and scalable graph learning pipeline for discovering novel biomedical knowledge in iBKH. As a proof of concept, we performed our iBKH-based method for computational in-silico drug repurposing for Alzheimer’s disease. The iBKH is publicly available.

从生物实验和临床实践中获得的丰富的生物医学知识是生物医学的宝贵资源。新兴的生物医学知识图谱（BKG）提供了一种高效且有效的方法来管理生物医学和生命科学领域的丰富知识。在这项研究中，我们通过协调和整合来自不同生物医学资源的信息，创建了一个名为综合生物医学知识中心（iBKH）的综合 BKG。为了使 iBKH 能够轻松地用于生物医学研究，我们开发了一个基于网络、用户友好的图形门户，允许快速、交互式的知识检索。此外，我们还实现了高效且可扩展的图形学习管道，用于在 iBKH 中发现新颖的生物医学知识。作为概念证明，我们执行了基于 iBKH 的方法，用于计算计算机模拟药物重新利用以治疗阿尔茨海默病。iBKH 是公开的。