1 citations · 1 across the 5 of their papers we have counts for
7 papers
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…
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…
BioMedGPT-Mol: Multi-task Learning for Molecular Understanding and Generation
Chenyang Zuo, Siqi Fan, Zaiqing Nie
Molecules play a crucial role in biomedical research and discovery, particularly in the field of small molecule drug development. Given the rapid advancements in large language mod…
PharMolixFM: All-Atom Foundation Models for Molecular Modeling and Generation
Yizhen Luo, Jiashuo Wang, Siqi Fan +1
Structural biology relies on accurate three-dimensional biomolecular structures to advance our understanding of biological functions, disease mechanisms, and therapeutics. While re…
OCSU: Optical Chemical Structure Understanding for Molecule-centric Scientific Discovery
Siqi Fan, Yuguang Xie, Bowen Cai +5
Understanding the chemical structure from a graphical representation of a molecule is a challenging image caption task that would greatly benefit molecule-centric scientific discov…