10 citations · 19 across the 4 of their papers we have counts for
4 papers
Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction
Jiahua Rao, Shuangjia Zheng, Sijie Mai +1
Illuminating the interconnections between drugs and genes is an important topic in drug development and precision medicine. Currently, computational predictions of drug-gene intera…
Learning Attributed Graph Representations with Communicative Message Passing Transformer
Jianwen Chen, Shuangjia Zheng, Ying Song +2
Constructing appropriate representations of molecules lies at the core of numerous tasks such as material science, chemistry and drug designs. Recent researches abstract molecules…
Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction
Jiahua Rao, Shuangjia Zheng, Yuedong Yang
Advances in machine learning have led to graph neural network-based methods for drug discovery, yielding promising results in molecular design, chemical synthesis planning, and mol…
Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks
Shuangjia Zheng, Jiahua Rao, Zhongyue Zhang +2
Synthesis planning is the process of recursively decomposing target molecules into available precursors. Computer-aided retrosynthesis can potentially assist chemists in designing…