Mr. Yi-Heng Zhu received the BS degree in computer science and technology from Nanjing Institute of Technology in 2015. From 2015 to 2023, he was a Ph.D student with the School of Computer Science and Engineering, Nanjing University of Science and Technology and a member of Pattern Recognition and Bioinformatics Group, led by Professor Dong-Jun Yu. From 2019 to 2021, he acted as a visiting student at the University of Michigan (Ann Arbor) in U.S.A, funded by China Scholarship Council and led by Professor Yang Zhang. He is currently a teacher with the College of Artificial Intelligence, Nanjing Agricultural University, and a member of Center for Data Science and Intelligent Computing, led by Professor Zhiwei Ji. He is interested in the following topics:

• Protein Function Prediction [Papers]

• Protein-Ligand Binding Sites Prediction [Papers]

• Protein Crystallization Prediction [Papers]

• Protein-Drug Interation Prediction [Papers]

• Protein-Protein Interation Prediction [Papers]

• Protein-Ligand Binding Affinity Prediction

• Transcription Factor Prediction [Papers]

• Large Language Model in Bioinformatics [Papers]

• Work Presentations

• Web Servers

• 2011.09-2015.06,   Nanjing Institute of Technology,   Computer Science and Technology,   Bachelor

• 2015.09-2017.06,   Nanjing University of Science and Technology,   Computer Technology,   Master

• 2017.09-2023.04,   Nanjing University of Science and Technology,   Control Science and Engineering,   Doctor

• 2019.12-2021.12,   University of Michigan,   Computational Medicine and Bioinformatics,   Visiting Scholar

Awards and Honors

• National Natural Science Foundation of China (Youth Program), No.62402227, 2025-2027.

• The Award of China Scholarship Council (2019-2021)

• The First Prize Scholarship in Nanjing University of Science and Technology (2019)

• The Second Prize Scholarship in Nanjing University of Science and Technology (2018)

Published Papers

• Yi-Heng Zhu, Zi Liu, Yu Ding, Zhiwei Ji*, Dong-Jun Yu*. Machine Learning for Protein Function Prediction. Book Chapter. Elsevier, 2024, In press.

• Yi-Heng Zhu, Zi Liu, Zhiwei Ji*, Dong-Jun Yu*. ULDNA: Integrating Unsupervised Multi-Source Language Models with LSTM-Attention Network for High-Accuracy Protein-DNA Binding Site Prediction. Briefings in Bioinformatics. 2024, 25(2):bbae040. [Download Citation with Endnote or BibTex Format] [DOI:10.1093/bib/bbae040] [PDF] [Support Information] [Web Server] [Source Code]

• Yi-Heng Zhu, Chengxin Zhang, Dongjun Yu*, Yang Zhang*. Integrating Unsupervised Language Model with Triplet Neural Networks for Protein Gene Ontology Prediction. PLOS Computational Biology. 2022, 18(12): e1010793. [Download Citation with Endnote or BibTex Format] [DOI:10.1371/journal.pcbi.1010793] [PDF] [Support Information] [Web Server] (This work was done collaboratively by researchers from Nanjing University of Science and Technology, and University of Michigan (Ann Arbor))

• Yi-Heng Zhu, Chengxin Zhang, Yan Liu, Gilbert Omenn, Peter Freddolino, Dongjun Yu*, Yang Zhang*. TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction. Genomics, Proteomics & Bioinformatics. 2022, 20(5): 1013-1027. [Download Citation with Endnote or BibTex Format] [DOI:10.1016/j.gpb.2022.03.001] [PDF] [Support Information] [Web Server] (This work was done collaboratively by researchers from Nanjing University of Science and Technology, and University of Michigan (Ann Arbor))

• Yi-Heng Zhu, Jun Hu, Fang Ge, Fuyi Li, Jiangning Song*, Yang Zhang*, Dong-Jun Yu*. Accurate Multi-Stage Prediction of Protein Crystallization Propensity Using Deep-Cascade Forest with Sequence-Based Features. Briefings in Bioinformatics. 2021, 22(3): bbaa076. [Download Citation with Endnote or BibTex Format] [DOI:10.1093/bib/bbaa076] [PDF] [Support Information] [Web Server] (This work was done collaboratively by researchers from Nanjing University of Science and Technology, Monash University, and University of Michigan (Ann Arbor))

• Yi-Heng Zhu, Jun Hu, Xiao-Ning Song, Dong-Jun Yu. DNAPred: Accurate Identification of DNA-binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines. Journal of Chemical Information and Modeling. 2019, 59:3057-3071. [Download Citation with Endnote or BibTex Format] [DOI:10.1021/acs.jcim.8b00749] [PDF] [Support Information] [Web Server]

• Yi-Heng Zhu, Jun Hu, Yong Qi, Xiao-Ning Song, Dong-Jun Yu. Boosting Granular Support Vector Machines for the Accurate Prediction of Protein-Nucleotide Binding Sites. Combinatorial Chemistry & High Throughput Screening. 2019, 22(7):455-469. [Download Citation with Endnote or BibTex Format] [DOI:10.2174/1386207322666190925125524] [PDF] [Web Server]

• Peng-Hao Wang#, Yi-Heng Zhu#, Xibei Yang, Dong-Jun Yu. GCmapCrys: Integrating Graph Attention Network with Predicted Contact Map for Multi-Stage Protein Crystallization Propensity Prediction. Analytical Biochemistry. 2023, 663: 115020. [Download Citation with Endnote or BibTex Format] [DOI:10.1016/j.ab.2022.115020] [PDF] [Code]

• Zi Liu#, Yi-Heng Zhu#, Long-Chen Shen, Xuan Xiao, Wang-Ren Qiu, Dong-Jun Yu. Integrating Unsupervised Language Model with Multi-View Multiple Sequence Alignments for High-Accuracy Inter-Chain Contact Prediction. Computers in Biology and Medicine. 2023, 166: 107529. [Download Citation with Endnote or BibTex Format] [DOI:10.1016/j.compbiomed.2023.107529] [PDF] [Support Information] [Code]

• Jiashun Wu, Yan Liu, Yi-Heng Zhu, Dong-Jun Yu. Improving Antifreeze Proteins Prediction with Protein Language Models and Hybrid Feature Extraction Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2024. In Press.

• Yunpeng Xia, Ying Zhang, Dian Liu, Yi-Heng Zhu, Zhikang Wang, Jiangning Song, Dong-Jun Yu. BLAM6A-Merge: Leveraging Attention Mechanisms and Feature Fusion Strategies to Improve the Identification of RNA N6-methyladenosine Sites. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2024. In Press.

• Yan Liu, Ken Han, Yi-Heng Zhu, Ying Zhang, Long-Chen Shen, Jiangning Song, Dong-Jun Yu*. Improving protein fold recognition using triplet network and ensemble deep learning. Briefings in Bioinformatics. 2021, 22(6): bbab248.

• Yan Liu, Yi-Heng Zhu, Xiaoning Song, Jiangning Song*, Dong-Jun Yu*. Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation. Briefings in Bioinformatics. 2021, 22(5): bbab001.

• Fang Ge, Jun Hu, Yi-Heng Zhu, Muhammad Arif, Dong-Jun Yu*. TargetMM: accurate missense mutation prediction by utilizing local and global sequence information with classifier ensemble. Combinatorial Chemistry & High Throughput Screening. 2022, 25(1): 38-52.

• Fang Ge, Yi-Heng Zhu, Jian Xu, Arif Muhammad, Jiangning Song*, and Dong-Jun Yu*. MutTMPredictor: robust and accurate cascade XGBoost classifier for prediction of disease-associated mutations in transmembrane proteins. Computational and Structural Biotechnology Journal. 2021, 19: 6400-6416.

• Ke Han, Long-Chen Shen, Yi-Heng Zhu, Jian Xu, Jiangning Song*, and Dong-Jun Yu*. MAResNet: predicting transcript factor binding sites by combining multi-scale bottom-up and top-down attention and residual network. Briefings in Bioinformatics. 2022, 23(1): bbab445.

• Jun Hu, Liang Rao, Yi-Heng Zhu, Gui-Jun Zhang, Dong-Jun Yu*. TargetDBP+: Enhancing the Performance of Identifying DNA-Binding Proteins via Weighted Convolutional Features. Journal of Chemical Information and Modeling. 2021, 61(1): 505-515.

• Ming-Cai Chen, Yang Li, Yi-Heng Zhu, Fang Ge, Dong-Jun Yu*. SSCpred: Single-Sequence-Based Protein Contact Prediction Using Deep Fully Convolutional Network. Journal of Chemical Information and Modeling. 2020, 60(6): 3295-3303.

• Jun Hu, Xiao-Gen Zhou, Yi-Heng Zhu, Dong-Jun Yu, Guijun Zhang. TargetDBP: Accurate DNA-Binding Protein Prediction via Sequence-based Multi-View Feature Learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2019, 17(4): 1419-1429.

• Dong-Jun Yu, Yi-Heng Zhu, Jun Hu. An Overview of Biocomputing Methods of Targeting Protein-Ligand Binding Residues. Journal of Data Acquisition and Processing. 2018, 33(2):195-206.

• Yi-Heng Zhu, Chengxin Zhang, Rucheng Diao, Xiaogen Zhou, Peter Freddolino*, Dongjun Yu*, Yang Zhang* . MetaGOPlus: Improving Gene Ontology Prediction of Proteins Using Deep Residual Network with Hierarchical Classification. The 28th Conference on Intelligent Systems for Molecular Biology (ISMB 2020). [PDF] [Support Information] [Link]

• Xiao-Rong Bao, Yi-Heng Zhu, and Dong-Jun Yu*. DeepTF: Accurate Prediction of Transcription Factor Binding Sites from DNA Sequence by Combining Multi-Scale Convolutional Neural Network and Long Short-Term Memory Neural Network. International Conference on Intelligence Science and Big Data Engineering (IScIDE 2019). [PDF] [Download Citation with Endnote or BibTex Format] [DOI:10.1007/978-3-030-36204-1_10]

Journal Reviewer

• Briefings in Bioinformatics

• IEEE-ACM Transactions on Computational Biology and Bioinformatics

• Journal of Cheminformatics

• BMC Bioinformatics

• Science Reports

• Computational and Structural Biotechnology Journal

Course

• Algorithm Design and Analysis [Teaching Materials]

• Computer Operating System [Teaching Materials]

• Bioinformatics [Teaching Materials]

• Python Programming [Teaching Materials]

• VB.NET Programming [Teaching Materials]

• IT Fundamentals [Teaching Materials]