23 citations · 52 across the 5 of their papers we have counts for
5 papers
Uni-Mol2: Exploring Molecular Pretraining Model at Scale
Xiaohong Ji, Zhen Wang, Zhifeng Gao +4
In recent years, pretraining models have made significant advancements in the fields of natural language processing (NLP), computer vision (CV), and life sciences. The significant…
Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction
Zhifeng Gao, Xiaohong Ji, Guojiang Zhao +4
Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in d…
Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?
Gengmo Zhou, Zhifeng Gao, Zhewei Wei +2
Molecular conformation generation (MCG) is a fundamental and important problem in drug discovery. Many traditional methods have been developed to solve the MCG problem, such as sys…
Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking?
Yuejiang Yu, Shuqi Lu, Zhifeng Gao +2
Molecular docking, given a ligand molecule and a ligand binding site (called ``pocket'') on a protein, predicting the binding mode of the protein-ligand complex, is a widely used t…
3D Molecular Generation via Virtual Dynamics
Shuqi Lu, Lin Yao, Xi Chen +3
Structure-based drug design, i.e., finding molecules with high affinities to the target protein pocket, is one of the most critical tasks in drug discovery. Traditional solutions,…