RDBridge

RDBridge: Rare Disease Knowledge Graph and Analytical Platform

RDBridge constructs and queries a large-scale knowledge graph of rare diseases by applying text mining to extract and structure entity relationships across biomedical domains.

Key Features:

• Comprehensive Knowledge Graph: Integrates text-mined relationships among genes, potential drugs, biological pathways, scientific literature, and medical imaging data into a structured rare disease network.
• Cross-Domain Search: Enables querying of genes, candidate therapeutics, pathways, publications, and imaging-associated data within the unified knowledge graph.
• Data Integration for Mechanistic and Translational Research: Connects heterogeneous biomedical entities to support pathogenesis analysis, hypothesis generation, and therapeutic target identification.
• Clinical Data Support: Links molecular, literature, and imaging data to inform diagnostic assessment and treatment strategy exploration.

Scientific Applications:

• Rare Disease Pathogenesis and Drug Discovery: Supports mechanistic studies, target prioritization, and translational research in rare diseases with limited epidemiological and publication data.
• Clinical Decision Support Research: Facilitates integration of molecular and clinical evidence to investigate diagnostic and therapeutic approaches.

Methodology:

Applies large-scale text mining to biomedical literature and related data sources to extract entity relationships, standardizes and integrates heterogeneous datasets, and represents them as a structured knowledge graph for rare disease research.