1 citations · 2 across the 4 of their papers we have counts for
7 papers
CONFIDE: Hallucination Assessment for Reliable Biomolecular Structure Prediction and Design
Zijun Gao, Mutian He, Shijia Sun +8
Reliable evaluation of protein structure predictions remains challenging, as metrics like pLDDT capture energetic stability but often miss subtle errors such as atomic clashes or c…
Learning the PTM Code through a Coarse-to-Fine, Mechanism-Aware Framework
Jingjie Zhang, Hanqun Cao, Zijun Gao +8
Post-translational modifications (PTMs) form a combinatorial "code" that regulates protein function, yet deciphering this code - linking modified sites to their catalytic enzymes -…
From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning?
Hanqun Cao, Hongrui Zhang, Junde Xu +12
Protein language models (PLMs) have advanced computational protein science through large-scale pretraining and scalable architectures. In parallel, reinforcement learning (RL) has…
A deep reinforcement learning platform for antibiotic discovery
Hanqun Cao, Marcelo D. T. Torres, Jingjie Zhang +8
Antimicrobial resistance (AMR) is projected to cause up to 10 million deaths annually by 2050, underscoring the urgent need for new antibiotics. Here we present ApexAmphion, a deep…
Lightweight MSA Design Advances Protein Folding From Evolutionary Embeddings
Hanqun Cao, Xinyi Zhou, Zijun Gao +7
Protein structure prediction often hinges on multiple sequence alignments (MSAs), which underperform on low-homology and orphan proteins. We introduce PLAME, a lightweight MSA desi…
SAGEPhos: Sage Bio-Coupled and Augmented Fusion for Phosphorylation Site Detection
Jingjie Zhang, Hanqun Cao, Zijun Gao +2
Phosphorylation site prediction based on kinase-substrate interaction plays a vital role in understanding cellular signaling pathways and disease mechanisms. Computational methods…