1 citations · 4 across the 13 of their papers we have counts for
14 papers
Towards Scalable Context-Aware Single-Cell Spatial Transcriptomics Prediction from Histology Images
Zijun Gao, Chunbin Gu, Jinxi Xiang +2
Predicting gene expression from H&E-stained histology images offers a scalable alternative to costly spatial transcriptomics, yet most existing methods operate at the spot level, w…
SF-Cluster: Frustration-Guided MSA Subsampling for Alternative Protein Conformation Recovery
Hanqun Cao, Zijun Gao, Chunbin Gu +3
Deep-learning structure predictors are sensitive to their multiple sequence alignment (MSA) input, making MSA subsampling a practical route to recovering alternative conformations.…
GeoCycler: Reward-Aligned 3D Diffusion for Constraint-Conditioned Cyclic Peptide Design
Jingjie Zhang, Hanqun Cao, Haosen Shi +10
Cyclic peptides are attractive therapeutic modalities because their closed-ring topology can improve stability and target specificity. However, de novo cyclic peptide design remain…
Does Engram Do Memory Retrieval in Autoregressive Image Generation?
Jinghao Wang, Qiyuan He, Chunbin Gu +1
The Engram module -- a hash-keyed, O(1) associative memory injected into Transformer layers -- was recently shown to improve large language model pretraining, with the appealing in…
CA-DEL: An Open Multi-Target, Multi-Modal Benchmark for Learning from DNA-Encoded Library Screens
Mutian He, Hanqun Cao, Cheng Tan +4
The success of machine learning in drug discovery hinges on learning the relationship between a chemical structure and its biological activity. While DNA-Encoded Library (DEL) tech…
Bi-TEAM: A Unified Cross-Scale Representation Learning Framework for Chemically Modified Biomolecules
Chunbin Gu, Zijun Gao, Mutian He +8
Representation learning for protein biochemical space faces a difficult trade-off: protein language models excel at capturing long-range biological semantics but often miss fine-gr…
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…
Lost in Tokenization: Context as the Key to Unlocking Biomolecular Understanding in Scientific LLMs
Kai Zhuang, Jiawei Zhang, Yumou Liu +10
Scientific Large Language Models (Sci-LLMs) have emerged as a promising frontier for accelerating biological discovery. However, these models face a fundamental challenge when proc…
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 -…
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…
DEL-Ranking: Ranking-Correction Denoising Framework for Elucidating Molecular Affinities in DNA-Encoded Libraries
Hanqun Cao, Mutian He, Ning Ma +3
DNA-encoded library (DEL) screening has revolutionized the detection of protein-ligand interactions through read counts, enabling rapid exploration of vast chemical spaces. However…
Unlocking Potential Binders: Multimodal Pretraining DEL-Fusion for Denoising DNA-Encoded Libraries
Chunbin Gu, Mutian He, Hanqun Cao +3
In the realm of drug discovery, DNA-encoded library (DEL) screening technology has emerged as an efficient method for identifying high-affinity compounds. However, DEL screening fa…