ExPath offers a novel graph learning framework that explains biological pathways by integrating experimental data with molecular interactions.

• Transforms complex biological knowledge base analysis into an interpretable graph learning task
• Incorporates protein language models and amino acid sequences for deeper biological insights
• Enables more targeted pathway identification without requiring extensive biological expertise
• Bridges the gap between raw experimental data and meaningful biological interpretation

This innovation matters because it democratizes pathway analysis, potentially accelerating discoveries in disease mechanisms, drug development, and precision medicine by extracting meaningful biological pathways from complex data.

Original Paper: ExPath: Towards Explaining Targeted Pathways for Biological Knowledge Bases