4 citations · 6 across the 8 of their papers we have counts for
8 papers
Rank-and-Reason: Multi-Agent Collaboration Accelerates Zero-Shot Protein Mutation Prediction
Yang Tan, Yuanxi Yu, Can Wu +7
Zero-shot mutation prediction is vital for low-resource protein engineering, yet existing protein language models (PLMs) often yield statistically confident results that ignore fun…
Sequence-Only Prediction of Binding Affinity Changes: A Robust and Interpretable Model for Antibody Engineering
Chen Liu, Mingchen Li, Yang Tan +3
A pivotal area of research in antibody engineering is to find effective modifications that enhance antibody-antigen binding affinity. Traditional wet-lab experiments assess mutants…
VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning
Yang Tan, Chen Liu, Jingyuan Gao +8
Natural language processing (NLP) has significantly influenced scientific domains beyond human language, including protein engineering, where pre-trained protein language models (P…
CPE-Pro: A Structure-Sensitive Deep Learning Method for Protein Representation and Origin Evaluation
Wenrui Gou, Wenhui Ge, Yang Tan +3
Protein structures are important for understanding their functions and interactions. Currently, many protein structure prediction methods are enriching the structure database. Disc…
A PLMs based protein retrieval framework
Yuxuan Wu, Xiao Yi, Yang Tan +3
Protein retrieval, which targets the deconstruction of the relationship between sequences, structures and functions, empowers the advancing of biology. Basic Local Alignment Search…
Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models
Yang Tan, Mingchen Li, Bingxin Zhou +7
Fine-tuning Pre-trained protein language models (PLMs) has emerged as a prominent strategy for enhancing downstream prediction tasks, often outperforming traditional supervised lea…
PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications
Yang Tan, Mingchen Li, Pan Tan +4
Large protein language models are adept at capturing the underlying evolutionary information in primary structures, offering significant practical value for protein engineering. Co…
MedChatZH: a Better Medical Adviser Learns from Better Instructions
Yang Tan, Mingchen Li, Zijie Huang +2
Generative large language models (LLMs) have shown great success in various applications, including question-answering (QA) and dialogue systems. However, in specialized domains li…