Supervised Deep Canonical Correlation Analysis for Multiview Feature Learning. - Yan Liu 038; Yun Li 010; Yunhao Yuan 001; Ji-Peng Qiang; Min Ruan; Zhao Zhang 018 (ICONIP (6), 2017)

A Complete Canonical Correlation Analysis for Multiview Learning. - Yan Liu 038; Yun Li 010; Yunhao Yuan 001 (ICIP, 2018)

A New Robust Deep Canonical Correlation Analysis Algorithm for Small Sample Problems. - Yan Liu 038; Yun Li 010; Yunhao Yuan 001; Hui Zhang (IEEE Access, 2019)

A simple and effective postprocessing method for image classification. - Yan Liu 038; Yun Li 010; Yunhao Yuan 001; Jipeng Qiang (CoRR, 2019)

Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites. - Ying Zhang 053; Yan Liu 038; Jian Xu 009; Xiaoyu Wang 016; Xinxin Peng; Jiangning Song; Dong-Jun Yu (Briefings Bioinform., 2021)

Improving protein fold recognition using triplet network and ensemble deep learning. - Yan Liu 038; Ke Han; Yi-Heng Zhu 001; Ying Zhang 053; Long-Chen Shen; Jiangning Song; Dong-Jun Yu (Briefings Bioinform., 2021)

Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation. - Yan Liu 038; Yi-Heng Zhu 001; Xiaoning Song; Jiangning Song; Dong-Jun Yu (Briefings Bioinform., 2021)

SAResNet: self-attention residual network for predicting DNA-protein binding. - Long-Chen Shen; Yan Liu 038; Jiangning Song; Dong-Jun Yu (Briefings Bioinform., 2021)

Enhancing Characteristic Gene Selection and Tumor Classification by the Robust Laplacian Supervised Discriminative Sparse PCA. - Lu-Xing Zhang; He Yan; Yan Liu 038; Jian Xu 009; Jiangning Song; Dong-Jun Yu (J. Chem. Inf. Model., 2022)

Learning Protein Embedding to Improve Protein Fold Recognition Using Deep Metric Learning. - Guan-Yu Zhu; Yan Liu 038; Peng-Hao Wang; Xibei Yang; Dong-Jun Yu (J. Chem. Inf. Model., 2022)

TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction. - Yi-Heng Zhu 001; Chengxin Zhang; Yan Liu 038; Gilbert S. Omenn; Peter L. Freddolino; Dong-Jun Yu; Yang Zhang 040 (Genom. Proteom. Bioinform., 2022)

Learning Cell Annotation under Multiple Reference Datasets by Multisource Domain Adaptation. - Yan Liu 038; He Yan; Long-Chen Shen; Dong-Jun Yu (J. Chem. Inf. Model., 2023)

TripletCell: a deep metric learning framework for accurate annotation of cell types at the single-cell level. - Yan Liu 038; Guo Wei; Chen Li 021; Long-Chen Shen; Robin B. Gasser; Jiangning Song; Dijun Chen; Dong-Jun Yu (Briefings Bioinform., 2023)

Prediction of protein-ATP binding residues using multi-view feature learning via contextual-based co-attention network. - Jia-Shun Wu; Yan Liu 038; Fang Ge; Dong-Jun Yu (Comput. Biol. Medicine, 2024)

Improving Antifreeze Proteins Prediction With Protein Language Models and Hybrid Feature Extraction Networks. - Jiashun Wu; Yan Liu 038; Yiheng Zhu 001; Dong-Jun Yu (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)

GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference. - Shuo Li; Yan Liu 038; Long-Chen Shen; He Yan; Jiangning Song; Dong-Jun Yu (Briefings Bioinform., 2024)

ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein-DNA binding site prediction. - Yi-Heng Zhu 001; Zi Liu; Yan Liu 038; Zhiwei Ji; Dong-Jun Yu (Briefings Bioinform., 2024)

CTISL: a dynamic stacking multi-class classification approach for identifying cell types from single-cell RNA-seq data. - Xiao Wang; Ziyi Chai; Shaohua Li; Yan Liu 038; Chen Li 021; Yu Jiang; Quanzhong Liu (Bioinform., 2024)

Robust GEPSVM classifier: An efficient iterative optimization framework. - He Yan; Yan Liu 038; Yanmeng Li; Qiaolin Ye; Dong-Jun Yu; Yong Qi (Inf. Sci., 2024)

TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion. - Zihao Yan; Fang Ge; Yan Liu 038; Yumeng Zhang; Fuyi Li; Jiangning Song; Dong-Jun Yu (J. Chem. Inf. Model., 2024)

scRCA: A Siamese network-based pipeline for annotating cell types using noisy single-cell RNA-seq reference data. - Yan Liu 038; Chen Li 021; Long-Chen Shen; He Yan; Guo Wei; Robin B. Gasser; Xiaohua Hu 001; Jiangning Song; Dong-Jun Yu (Comput. Biol. Medicine, 2025)

Supervised contrastive learning enhances MHC-II peptide binding affinity prediction. - Long-Chen Shen; Yan Liu 038; Zi Liu; Yumeng Zhang; Zhikang Wang; Yuming Guo 001; Jamie Rossjohn; Jiangning Song; Dong-Jun Yu (Expert Syst. Appl., 2025)

Identifying Protein-Nucleotide Binding Residues via Grouped Multi-task Learning and Pre-trained Protein Language Models. - Jiashun Wu; Yan Liu 038; Ying Zhang 053; Xiaoyu Wang 016; He Yan; Yiheng Zhu 001; Jiangning Song; Dong-Jun Yu (J. Chem. Inf. Model., 2025)

Progressive Document-level Text Simplification via Large Language Models. - Dengzhao Fang; Jipeng Qiang; Yi Zhu 006; Yun-Hao Yuan 001; Wei Li; Yan Liu 038 (CoRR, 2025)

Identification of Protein-Nucleotide Binding Residues With Deep Multi-Task and Multi-Scale Learning. - Jiashun Wu; Fang Ge; Shanruo Xu; Yan Liu 038; Jiangning Song; Dong-Jun Yu (IEEE J. Biomed. Health Informatics, 2025)