6 papers
Validation of an LLM-based Multi-Agent Framework for Protein Engineering in Dry Lab and Wet Lab
Zan Chen, Yungeng Liu, Yu Guang Wang +1
Recent advancements in Large Language Models (LLMs) have enhanced efficiency across various domains, including protein engineering, where they offer promising opportunities for dry…
TourSynbio-Search: A Large Language Model Driven Agent Framework for Unified Search Method for Protein Engineering
Yungeng Liu, Zan Chen, Yu Guang Wang +1
The exponential growth in protein-related databases and scientific literature, combined with increasing demands for efficient biological information retrieval, has created an urgen…
A Regressor-Guided Graph Diffusion Model for Predicting Enzyme Mutations to Enhance Turnover Number
Xiaozhu Yu, Kai Yi, Yu Guang Wang +1
Enzymes are biological catalysts that can accelerate chemical reactions compared to uncatalyzed reactions in aqueous environments. Their catalytic efficiency is quantified by the t…
A Survey for Large Language Models in Biomedicine
Chong Wang, Mengyao Li, Junjun He +14
Recent breakthroughs in large language models (LLMs) offer unprecedented natural language understanding and generation capabilities. However, existing surveys on LLMs in biomedicin…
TourSynbio: A Multi-Modal Large Model and Agent Framework to Bridge Text and Protein Sequences for Protein Engineering
Yiqing Shen, Zan Chen, Michail Mamalakis +6
The structural similarities between protein sequences and natural languages have led to parallel advancements in deep learning across both domains. While large language models (LLM…
A Fine-tuning Dataset and Benchmark for Large Language Models for Protein Understanding
Yiqing Shen, Zan Chen, Michail Mamalakis +6
The parallels between protein sequences and natural language in their sequential structures have inspired the application of large language models (LLMs) to protein understanding.…