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IEEE Journal of Biomedical and Health Informatics|October 26, 2021
NPI-RGCNAE: Fast Predicting ncRNA-Protein Interactions Using the Relational Graph Convolutional Network Auto-EncoderHan Yu, Zi-Ang Shen, Pu-Feng DuCurrent Gene Therapy|July 13, 2021
Recent Advances in Predicting Protein-lncRNA Interactions Using Machine Learning MethodsHan Yu, Zi-Ang Shen, Yuan-Ke Zhou, et al.Briefings in Bioinformatics|April 6, 2021
NPI-GNN: Predicting ncRNA-protein interactions with deep graph neural networksZi-Ang Shen, Tao Luo, Yuan-Ke Zhou, et al.Frontiers in Genetics|February 11, 2020
Predicting lncRNA-Protein Interactions With miRNAs as Mediators in a Heterogeneous Network ModelYuan-Ke Zhou, Zi-Ang Shen, Han Yu, et al.Frontiers in Genetics|November 16, 2020
DPPN-SVM: Computational Identification of Mis-Localized Proteins in Cancers by Integrating Differential Gene Expressions With Dynamic Protein-Protein Interaction NetworksGuang-Ping Li, Pu-Feng Du, Zi-Ang Shen, et al.Frontiers in Genetics|December 28, 2020
LPI-SKF: Predicting lncRNA-Protein Interactions Using Similarity Kernel FusionsYuan-Ke Zhou, Jie Hu, Zi-Ang Shen, et al.Current Genomics|October 31, 2017
Predicting Protein Submitochondrial Locations: The 10th AnniversaryPu-Feng DuJournal of Theoretical Biology|December 26, 2015
Predicting Golgi-resident protein types using pseudo amino acid compositions: Approaches with positional specific physicochemical propertiesYa-Sen Jiao, Pu-Feng DuBriefings in Bioinformatics|April 6, 2025
scMUG: deep clustering analysis of single-cell RNA-seq data on multiple gene functional modulesDe-Min Liang, Pu-Feng DuFrontiers in Genetics|March 4, 2025
WCSGNet: a graph neural network approach using weighted cell-specific networks for cell-type annotation in scRNA-seqYi-Ran Wang, Pu-Feng DuPageof 209