This research introduces a novel uncertainty-aware adaptation of Large Language Models (LLMs) to improve reliability in analyzing protein-protein interactions critical for disease understanding.

• Combines LLMs with uncertainty quantification to reduce false predictions in protein interaction analysis
• Implements a specialized framework for biomedical literature mining that provides confidence metrics with each prediction
• Demonstrates significant improvements in identifying reliable protein interactions for neurodegenerative disorders and cancer
• Enables more targeted drug development approaches through higher-confidence protein interaction mapping

This advancement matters for medical research by providing more trustworthy AI analysis tools, directly supporting precision medicine initiatives and reducing wasted laboratory resources on false leads.

Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis