STCGAN: a novel cycle-consistent generative adversarial network for spatial transcriptomics cellular deconvolution.
Briefings Bioinform., 2024
CSCL-DTI: predicting drug-target interaction through cross-view and self-supervised contrastive learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism.
Briefings Bioinform., September, 2023
Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks.
Briefings Bioinform., September, 2023
CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning.
Bioinform., August, 2023
An effective image fusion algorithm based on grey relation of similarity and morphology.
J. Ambient Intell. Humaniz. Comput., 2023
Interpretable multi-view attention network for drug-drug interaction prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
GELKcat: An Integration Learning of Substrate Graph with Enzyme Embedding for Kcat prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
Pre-training graph neural networks for link prediction in biomedical networks.
Bioinform., 2022
Association Mining to Identify Microbe Drug Interactions Based on Heterogeneous Network Embedding Representation.
IEEE J. Biomed. Health Informatics, 2021
Class similarity network for coding and long non-coding RNA classification.
BMC Bioinform., 2021
Graph contextualized attention network for predicting synthetic lethality in human cancers.
Bioinform., 2021
Predicting human microbe-disease associations via graph attention networks with inductive matrix completion.
Briefings Bioinform., 2021
NTSHMDA: Prediction of Human Microbe-Disease Association Based on Random Walk by Integrating Network Topological Similarity.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020
Deep learning based DNA: RNA triplex forming potential prediction.
BMC Bioinform., 2020
Predicting human microbe-drug associations via graph convolutional network with conditional random field.
Bioinform., 2020
Ensembling graph attention networks for human microbe-drug association prediction.
Bioinform., 2020
DL-CRISPR: A Deep Learning Method for Off-Target Activity Prediction in CRISPR/Cas9 With Data Augmentation.
IEEE Access, 2020
Predicting Drugs for COVID-19/SARS-CoV-2 via Heterogeneous Graph Attention Networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network.
BMC Bioinform., 2019