Biomedical discovery through the integrative biomedical knowledge hub (iBKH)

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. [Display omitted] •We build integrative biomedical knowledge Hub (iBKH), a comprehensive biomedical knowledge graph (BKG)•iBKH enables fast biomedical knowledge retrieval•We build a knowledge discovery pipeline based on machine learning and iBKH•A case study: iBKH-based knowledge discovery for Alzheimer’s disease drug repurposing Drugs; Bioinformatics; Systems biology