DeepTF: Accurate Prediction of Transcription Factor Binding Sites by Combining Multi-scale Convolution and Long Short-Term Memory Neural Network. - Xiao-Rong Bao; Yi-Heng Zhu 001; Dong-Jun Yu (IScIDE (2), 2019)

DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines. - Yi-Heng Zhu 001; Jun Hu 010; Xiaoning Song; Dong-Jun Yu (J. Chem. Inf. Model., 2019)

SSCpred: Single-Sequence-Based Protein Contact Prediction Using Deep Fully Convolutional Network. - Ming-Cai Chen; Yang Li 107; Yi-Heng Zhu 001; Fang Ge; Dong-Jun Yu (J. Chem. Inf. Model., 2020)

TargetDBP: Accurate DNA-Binding Protein Prediction Via Sequence-Based Multi-View Feature Learning. - Jun Hu 010; Xiaogen Zhou; Yi-Heng Zhu 001; Dong-Jun Yu; Gui-Jun Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

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)

Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features. - Yi-Heng Zhu 001; Jun Hu 010; Fang Ge; Fuyi Li; Jiangning Song; Yang Zhang 040; Dong-Jun Yu (Briefings Bioinform., 2021)

TargetDBP+: Enhancing the Performance of Identifying DNA-Binding Proteins via Weighted Convolutional Features. - Jun Hu 010; Liang Rao; Yi-Heng Zhu 001; Gui-Jun Zhang; Dong-Jun Yu (J. Chem. Inf. Model., 2021)

MAResNet: predicting transcription factor binding sites by combining multi-scale bottom-up and top-down attention and residual network. - Ke Han; Long-Chen Shen; Yi-Heng Zhu 001; Jian Xu 009; Jiangning Song; Dong-Jun Yu (Briefings Bioinform., 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)

Integrating unsupervised language model with triplet neural networks for protein gene ontology prediction. - Yi-Heng Zhu 001; Chengxin Zhang; Dong-Jun Yu; Yang Zhang 040 (PLoS Comput. Biol., 2022)

Integrating unsupervised language model with multi-view multiple sequence alignments for high-accuracy inter-chain contact prediction. - Zi Liu; Yi-Heng Zhu 001; Long-Chen Shen; Xuan Xiao; Wangren Qiu; Dong-Jun Yu (Comput. Biol. Medicine, 2023)

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)

BLAM6A-Merge: Leveraging Attention Mechanisms and Feature Fusion Strategies to Improve the Identification of RNA N6-Methyladenosine Sites. - Yunpeng Xia; Ying Zhang 053; Dian Liu; Yi-Heng Zhu 001; Zhikang Wang; Jiangning Song; Dong-Jun Yu (IEEE ACM Trans. Comput. Biol. 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)

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)