72 citations · 145 across the 7 of their papers we have counts for
5 papers · 1 filter
ZeroDDI: A Zero-Shot Drug-Drug Interaction Event Prediction Method with Semantic Enhanced Learning and Dual-Modal Uniform Alignment
Ziyan Wang, Zhankun Xiong, Feng Huang +2
Drug-drug interactions (DDIs) can result in various pharmacological changes, which can be categorized into different classes known as DDI events (DDIEs). In recent years, previousl…
Heterogeneous Causal Metapath Graph Neural Network for Gene-Microbe-Disease Association Prediction
Kexin Zhang, Feng Huang, Luotao Liu +4
The recent focus on microbes in human medicine highlights their potential role in the genetic framework of diseases. To decode the complex interactions among genes, microbes, and d…
Coefficient Decomposition for Spectral Graph Convolution
Feng Huang, Wen Zhang
Spectral graph convolutional network (SGCN) is a kind of graph neural networks (GNN) based on graph signal filters, and has shown compelling expressivity for modeling graph-structu…
HampDTI: a heterogeneous graph automatic meta-path learning method for drug-target interaction prediction
Hongzhun Wang, Feng Huang, Wen Zhang
Motivation: Identifying drug-target interactions (DTIs) is a key step in drug repositioning. In recent years, the accumulation of a large number of genomics and pharmacology data h…
Tensor Decomposition with Relational Constraints for Predicting Multiple Types of MicroRNA-disease Associations
Feng Huang, Xiang Yue, Zhankun Xiong +2
MicroRNAs (miRNAs) play crucial roles in multifarious biological processes associated with human diseases. Identifying potential miRNA-disease associations contributes to understan…