Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation. - Shuo Zhang 010; Lei Xie 006 (IJCAI, 2020)

Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures. - Shuo Zhang 010; Yang Liu; Lei Xie 006 (CoRR, 2020)

Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology. - Tian Cai; Li Xie 002; Muge Chen; Yang Liu; Di He 003; Shuo Zhang 010; Cameron Mura; Philip E. Bourne; Lei Xie 006 (CoRR, 2021)

Efficient and Accurate Physics-aware Multiplex Graph Neural Networks for 3D Small Molecules and Macromolecule Complexes. - Shuo Zhang 010; Yang Liu; Lei Xie 006 (CoRR, 2022)

Physics-aware Graph Neural Network for Accurate RNA 3D Structure Prediction. - Shuo Zhang 010; Yang Liu; Lei Xie 006 (CoRR, 2022)

Learning Universal and Robust 3D Molecular Representations with Graph Convolutional Networks. - Shuo Zhang 010; Yang Liu; Li Xie 002; Lei Xie 006 (CoRR, 2023)

A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems. - Shuo Zhang 010; Yang Liu; Lei Xie 006 (CoRR, 2023)

Protein Language Model-Powered 3D Ligand Binding Site Prediction from Protein Sequence. - Shuo Zhang 010; Lei Xie 006 (CoRR, 2023)

Optimization and Application of Graph Neural Networks - Shuo Zhang 010 (2023)

End-to-end sequence-structure-function meta-learning predicts genome-wide chemical-protein interactions for dark proteins. - Tian Cai; Li Xie 002; Shuo Zhang 010; Muge Chen; Di He 003; Amitesh Badkul; Yang Liu; Hari Krishna Namballa; Michael Dorogan; Wayne W. Harding; Cameron Mura; Philip E. Bourne; et al. (PLoS Comput. Biol., 2023)