Biomedical discovery through the integrative biomedical knowledge hub (iBKH).

Area of Science:

• Biomedical Informatics
• Knowledge Representation
• Data Integration

Background:

• Biomedical knowledge is rapidly expanding, necessitating advanced management systems.
• Biomedical knowledge graphs (BKGs) offer an effective approach to organize and utilize this data.
• Existing resources may lack comprehensiveness or ease of access for researchers.

Purpose of the Study:

• To create a comprehensive and integrated biomedical knowledge graph (iBKH).
• To develop a user-friendly portal for interactive knowledge retrieval from iBKH.
• To implement a scalable pipeline for discovering novel biomedical insights using iBKH.

Main Methods:

• Harmonizing and integrating data from diverse biomedical resources to build the iBKH.
• Developing a web-based graphical portal for accessible and interactive data exploration.
• Implementing a graph learning pipeline for advanced knowledge discovery and analysis.

Main Results:

• Successfully created the integrative Biomedical Knowledge Hub (iBKH), a comprehensive BKG.
• Developed an accessible, user-friendly web portal for efficient knowledge retrieval.
• Demonstrated the utility of iBKH for in-silico drug repurposing in Alzheimer's disease.

Conclusions:

• The iBKH provides a valuable, integrated resource for biomedical research.
• The developed tools enable efficient knowledge discovery and hypothesis generation.
• iBKH supports applications like drug repurposing, advancing biomedical innovation.