24 citations · 35 across the 7 of their papers we have counts for
5 papers · 1 filter
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022
Yusong Wang, Shaoning Li, Zun Wang +4
In the technical report, we provide our solution for OGB-LSC 2022 Graph Regression Task. The target of this task is to predict the quantum chemical property, HOMO-LUMO gap for a gi…
ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules
Yusong Wang, Shaoning Li, Xinheng He +6
Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular p…
Tailoring Molecules for Protein Pockets: a Transformer-based Generative Solution for Structured-based Drug Design
Kehan Wu, Yingce Xia, Yang Fan +7
Structure-based drug design is drawing growing attentions in computer-aided drug discovery. Compared with the virtual screening approach where a pre-defined library of compounds ar…
Multi-View Substructure Learning for Drug-Drug Interaction Prediction
Zimeng Li, Shichao Zhu, Bin Shao +3
Drug-drug interaction (DDI) prediction provides a drug combination strategy for systemically effective treatment. Previous studies usually model drug information constrained on a s…
Direct Molecular Conformation Generation
Jinhua Zhu, Yingce Xia, Chang Liu +9
Molecular conformation generation aims to generate three-dimensional coordinates of all the atoms in a molecule and is an important task in bioinformatics and pharmacology. Previou…