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Bioinformatics (Oxford, England)|July 17, 2026
Momentum contrast-enhanced multimodal representation learning for drug synergy predictionYu Gu, Xindi Huang, Lifen Shi, et al.IEEE/ACM Transactions on Computational Biology and Bioinformatics|June 10, 2021
RNPredATC: A Deep Residual Learning-Based Model With Applications to the Prediction of Drug-ATC Code AssociationHaochen Zhao, Guihua Duan, Peng Ni, et al.Bioinformatics (Oxford, England)|February 12, 2022
PDMDA: predicting deep-level miRNA-disease associations with graph neural networks and sequence featuresCheng Yan, Guihua Duan, Na Li, et al.Briefings in Bioinformatics|May 22, 2021
A survey on predicting microbe-disease associations: biological data and computational methodsZhongqi Wen, Cheng Yan, Guihua Duan, et al.IEEE/ACM Transactions on Computational Biology and Bioinformatics|April 21, 2020
Predicting Drug-Drug Interactions Based on Integrated Similarity and Semi-Supervised LearningCheng Yan, Guihua Duan, Yayan Zhang, et al.Journal of Ethnopharmacology|May 31, 2023
SMRGAT: A traditional Chinese herb recommendation model based on a multi-graph residual attention network and semantic knowledge fusionXiaoyan Yang, Changsong DingFrontiers in Neurology|August 7, 2023
Combining convolutional attention mechanism and residual deformable Transformer for infarct segmentation from CT scans of acute ischemic stroke patientsZhixiang Xu, Changsong DingFrontiers in Genetics|January 10, 2022
An Improved Deep Learning Model: S-TextBLCNN for Traditional Chinese Medicine Formula ClassificationNing Cheng, Yue Chen, Wanqing Gao, et al.Frontiers in Pharmacology|December 18, 2025
TCMRGAT: Relational graph attention networks for predicting stroke treatment efficacy of traditional Chinese medicine prescriptionsNing Cheng, Changsong Ding, Xuekun SongIEEE Journal of Biomedical and Health Informatics|December 15, 2025
MRHAF: Multi-Relational Hierarchical Attention with Hybrid Knowledge Fusion for Explainable Herb RecommendationsXiaoyan Yang, Yiyu Luo, Changsong DingPageof 89