16 citations · 60 across the 15 of their papers we have counts for
15 papers
Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning
Chen Tang, Yizhou Wang, Jianyu Wu +26
Structure-property relationships are foundational to biology, chemistry and materials science, where function, reactivity and physical response emerge from spatial, chemical and pe…
Self-evolving AI agents for protein discovery and directed evolution
Yang Tan, Lingrong Zhang, Mingchen Li +5
Protein scientific discovery is bottlenecked by the manual orchestration of information and algorithms, while general agents are insufficient in complex domain projects. VenusFacto…
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…
VenusX: Unlocking Fine-Grained Functional Understanding of Proteins
Yang Tan, Wenrui Gou, Bozitao Zhong +3
Deep learning models have driven significant progress in predicting protein function and interactions at the protein level. While these advancements have been invaluable for many b…
ReactZyme: A Benchmark for Enzyme-Reaction Prediction
Chenqing Hua, Bozitao Zhong, Sitao Luan +4
Enzymes, with their specific catalyzed reactions, are necessary for all aspects of life, enabling diverse biological processes and adaptations. Predicting enzyme functions is essen…
Autoregressive Enzyme Function Prediction with Multi-scale Multi-modality Fusion
Dingyi Rong, Wenzhuo Zheng, Bozitao Zhong +3
Accurate prediction of enzyme function is crucial for elucidating biological mechanisms and driving innovation across various sectors. Existing deep learning methods tend to rely s…