5 citations · 12 across the 10 of their papers we have counts for
5 papers · 1 filter
Structure-aware Reinforcement Learning for Protein Directed Evolution
Zikun Nie, Suyuan Zhao, Yizhen Luo +2
Protein optimization remains a longstanding goal in life sciences. Existing machine learning-assisted directed evolution (MLDE) methods primarily rely on sequence-only features, ov…
CellMSA: Context Modeling for Single-Cell Representation Learning
Suyuan Zhao, Minghao Liu, Yizhen Luo +1
Single-cell transcriptomics enables profiling of cellular states at unprecedented resolution, but its high dimensionality, sparsity, and technical batch effects pose significant ch…
AbGaze: Attentive Geometric Representation Learning for End-to-End Antibody Design
Jiashuo Wang, Siqi Fan, Yizhen Luo +1
Computational antibody design requires representations that capture the geometric patterns underlying antigen--antibody interactions, yet existing approaches often rely on scalar d…
Co-Generative De Novo Functional Protein Design
Xinrui Chen, Yizhen Luo, Siqi Fan +1
De novo functional protein design aims to generate protein sequences that realize specified biochemical functions without relying on evolutionary templates, enabling broad applicat…
Reinforced Reasoning for End-to-End Retrosynthetic Planning
Chenyang Zuo, Siqi Fan, Yizhen Luo +1
Retrosynthetic planning is a fundamental task in organic chemistry, yet remains challenging due to its combinatorial complexity. To address this, conventional approaches typically…