Protein Question Answering

Protein Question Answering (PQA) aims to leverage the power of large language models (LLMs) to answer complex scientific questions about proteins using both textual information and raw protein sequence data. Current research focuses on developing hybrid models that combine protein language models (PLMs) with LLMs, often employing techniques like chain-of-thought prompting to improve reasoning capabilities and address the challenge of integrating different data modalities. These advancements are enabling more accurate and comprehensive analysis of protein function and interactions, with potential applications ranging from drug discovery to understanding complex biological pathways. The development of specialized datasets and benchmark tasks is also driving progress in this rapidly evolving field.