10 citations · 47 across the 13 of their papers we have counts for
13 papers
Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation
Odin Zhang, Yufei Huang, Shichen Cheng +14
Most earlier 3D structure-based molecular generation approaches follow an atom-wise paradigm, incrementally adding atoms to a partially built molecular fragment within protein pock…
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
Tianyu Fan, Lirong Wu, Yufei Huang +4
Recent years have witnessed the great success of graph pre-training for graph representation learning. With hundreds of graph pre-training tasks proposed, integrating knowledge acq…
Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions
Rui Sun, Lirong Wu, Haitao Lin +2
Augmentation is an effective alternative to utilize the small amount of labeled protein data. However, most of the existing work focuses on design-ing new architectures or pre-trai…
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding
Lirong Wu, Yijun Tian, Yufei Huang +4
Protein-Protein Interactions (PPIs) are fundamental in various biological processes and play a key role in life activities. The growing demand and cost of experimental PPI assays r…
Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge
Yufei Huang, Odin Zhang, Lirong Wu +5
Accurate prediction of protein-ligand binding structures, a task known as molecular docking is crucial for drug design but remains challenging. While deep learning has shown promis…
PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction
Lirong Wu, Yufei Huang, Cheng Tan +5
Compound-Protein Interaction (CPI) prediction aims to predict the pattern and strength of compound-protein interactions for rational drug discovery. Existing deep learning-based me…