5 citations · 15 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering
Yungeng Liu, Zan Chen, Yu Guang Wang +1
Protein engineering is important for biomedical applications, but conventional approaches are often inefficient and resource-intensive. While deep learning (DL) models have shown p…
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.…