<ul><li>Large language models (LLMs) show potential for automating the extraction of molecular interactions in biological systems.</li><li>The study evaluates the effectiveness of various LLMs in recognizing protein interactions, identifying genes related to radiation-affected pathways, and delineating gene regulatory relationships.</li><li>Larger models demonstrate superior performance, particularly in extracting complex interactions among genes and proteins.</li><li>LLMs face challenges in identifying groups with diverse functions and recognizing highly correlated gene regulatory relationships.</li></ul>

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge

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