Min Zeng (曾 敏)
Assistant Professor
CSU-Bioinformatics Group
School of Computer Science and Engineering
Central South University

Location: Computer Building, Lusha Road #932, Yuelu District, Changsha, Hunan, China
About Me | Work Experience | Research Interests | Education | Publications | Grants | Services | Honors and Awards

Email: zengmin@csu.edu.cn
[中文主页] [Google Scholar] [ResearchGate] [GitHub]

About Me

I am currently an assistant professor in the School of Computer Science and Engineering, Central South University, P. R. China. My research interests include machine learning and deep learning techniques for bioinformatics and computational biology. I have published more than 20 technical papers in refereed journals such as Bioinformatics, Neurocomputing, BMC Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Methods, and conference proceedings such as ECCB, BIBM, APBC and ISBRA.

Work Experience


Research Interests

My research interests include machine learning and deep learning techniques for bioinformatics and computational biology. Currently, I focus on the following research topics:

Education


Publications

Journals:

  • Min Zeng, Fuhao Zhang, Fang-Xiang Wu, Yaohang Li, Jianxin Wang, Min Li*, “Protein–protein interaction site prediction through combining local and global features with deep neural networks,” Bioinformatics, 36 (4), 1114-1120, 2020. [PDF] [Code]
  • Min Zeng, Min Li*, Zhihui Fei, Ying Yu, Yi Pan, Jianxin Wang, “Automatic ICD-9 coding via deep transfer learning,” Neurocomputing, 324, 43-50, 2019. [PDF]
  • Min Zeng, Min Li*, Fang-Xiang Wu, Yaohang Li, Yi Pan, “DeepEP: a deep learning framework for identifying essential proteins,” BMC Bioinformatics, 20 (16), 506, 2019. [PDF] [Code]
  • Min Zeng, Min Li*, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Yi Pan, Jianxin Wang, “A deep learning framework for identifying essential proteins by integrating multiple types of biological information,” IEEE/ACM transactions on computational biology and bioinformatics (IEEE TCBB), DOI: 10.1109/TCBB.2019.2897679. [PDF] [Code]
  • Min Zeng, Chengqian Lu, Fuhao Zhang, Yiming Li, Fang-Xiang Wu, Yaohang Li, Min Li*, “SDLDA: lncRNA–disease association prediction based on singular value decomposition and deep learning,” Methods, DOI: 10.1016/j.ymeth.2020.05.002. [PDF] [Code]
  • Min Zeng, Chengqian Lu, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Jianxin Wang, Min Li*, “DMFLDA: A deep learning framework for predicting lncRNA–disease associations,” IEEE/ACM transactions on computational biology and bioinformatics (IEEE TCBB), DOI: 10.1109/TCBB.2020.2983958. [PDF] [Code]
  • Nian Wang#, Min Zeng#, Yiming Li, Fang-Xiang Wu, and Min Li*, “Essential protein prediction based on node2vec and XGBoost,” Journal of Computational Biology.
  • Chengqian Lu, Min Zeng, FangXiang Wu, Min Li, Jianxin Wang*, “Improving circRNA-disease association prediction by sequence and ontology representations with convolutional and recurrent neural networks,” Bioinformatics, DOI: 10.1093/bioinformatics/btaa1077.
  • Chengqian Lu, Min Zeng, Fuhao Zhang, FangXiang Wu, Min Li, Jianxin Wang*, “Deep matrix factorization improves prediction of human circRNA-disease associations,” IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), DOI: 10.1109/JBHI.2020.2999638. [PDF]
  • Yifan Wu, Min Zeng, Zhihui Fei, Ying Yu, Fang-Xiang Wu, Min Li*, “KAICD: A knowledge attention-based deep learning framework for automatic ICD coding,” Neurocomputing, DOI: 10.1016/j.neucom.2020.05.115. [PDF] [Code]
  • Xingyi Li, Wenkai Li, Min Zeng, Ruiqing Zheng, Min Li*, “Network-based methods for predicting essential genes or proteins: a survey,” Briefings in Bioinformatics (BIB), DOI: 10.1093/bib/bbz017. [PDF]
  • Min Li*, Zhihui Fei, Min Zeng, Fang-Xiang Wu, Yaohang Li, Yi Pan, Jianxin Wang, “Automated ICD-9 coding via a deep learning approach,” IEEE/ACM transactions on computational biology and bioinformatics (IEEE TCBB), DOI: 10.1109/TCBB.2018.2817488. [PDF]
  • Fuhao Zhang, Hong Song, Min Zeng, Yaohang Li, Lukasz Kurgan, Min Li*, “DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions,” Proteomics, 1900019, 2019. [PDF]
  • Fuhao Zhang, Hong Song, Min Zeng, Fang-Xiang Wu, Yaohang Li, Yi Pan, Min Li*, “A deep learning framework for gene ontology annotations with sequence- and network-based information,” IEEE/ACM transactions on computational biology and bioinformatics (IEEE TCBB), DOI: 10.1109/TCBB.2020.2968882. [PDF] [Code]
  • Shehu Mohammed Yusuf, Fuhao Zhang, Min Zeng, Min Li*, “DeepPPF: a deep learning framework for predicting protein family,” Neurocomputing, DOI: 10.1016/j.neucom.2020.11.062. [PDF] [Code]
  • Jiashuai Zhang, Wenkai Li, Min Zeng, Xiangmao Meng, Lukasz Kurgan, Fang-Xiang Wu, Min Li*, “NetEPD: a network-based essential protein discovery platform,” Tsinghua Science and Technology, 25 (4), 542-552, 2020. [PDF]
  • Fuhao Zhang, Wenbo Shi, Jian Zhang, Min Zeng, Min Li, Lukasz Kurgan*, “PROBselect: accurate prediction of proteinbinding residues from proteins sequences via dynamic predictor selection,” 19th European Conference on Computational Biology (ECCB2020), also appears in Bioinformatics, DOI: 10.1093/bioinformatics/btaa806. [PDF] [Web server]
  • Renyi Zhou, Zhangli Lu, Huimin Luo, Min Zeng, Min Li*, “NEDD: a network embedding based method for predicting drug-disease associations,” 18th Asia Pacific Bioinformatics Conference (APBC2020), also appears in BMC Bioinformatics, 21, 387 (2020). [PDF]
  • Kejuan Yue, Beiji Zou*, Lei Wang, Xiao Li, Min Zeng, Faran Wei, “Prediction of Drug-Drug Interactions Based on Multi-layer Feature Selection and Data Balance,” Chinese Journal of Electronics, 26(3), 585-590. [PDF]



Conferences:

  • Min Zeng, Min Li*, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Yi Pan, “A deep learning framework for identifying essential proteins based on protein-protein interaction network and gene expression data,” 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 583-588. [PDF]
  • Min Zeng, Chengqian Lu, Fuhao Zhang, Zhangli Lu, Fang-Xiang Wu, Yaohang Li, Min Li*, “LncRNA–disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques,” 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 577-582. [PDF] [Code]
  • Nian Wang#, Min Zeng#, Jiashuai Zhang, Yiming Li, Min Li*, “Ess-NEXG: Predict Essential Proteins by Constructing a Weighted Protein Interaction Network based on Node Embedding and XGBoost,” 16th International Symposium on Bioinformatics Research and Applications (ISBRA), 95-104. [PDF]
  • Min Zeng, Beiji Zou, Faran Wei, Xiyao Liu, Lei Wang*, “Effective prediction of three common diseases by combining SMOTE with Tomek links technique for imbalanced medical data,” 2016 IEEE International Conference of Online Analysis and Computing Science, 225-228. [PDF]
  • Zhangli Lu, Yake Wang, Min Zeng, Min Li*, “HNEDTI: Prediction of drug-target interaction based on heterogeneous network embedding,” 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 211-214. [PDF]
  • Faran Wei, Beiji Zou, Lei Wang*, Kejuan Yue, Min Zeng, Xiao Li, “MapReduce based parallel data processing for drug-drug interaction prediction,” Proceedings of the 2015 International Conference on Information Science and Cloud Computing, 2016. [PDF]
  • Xiao Li, Beiji Zou*, Lei Wang, Min Zeng, Kejuan Yue, Faran Wei, “A Novel LASSO-Based Feature weighting Selection method for Microarray Data Classification,” Proceedings of the IET International Conference on Biomedical Image and Signal Processing (ICBISP), 2015. [PDF]

Grants

  • PI:Graduate Innovation Fund of Central South University, “Research on Essential Protein Prediction Based on Deep Learning”, Grant No. 2019zzts281, Jan. 1, 2019 ~ Jun. 31, 2020.

Services

Conference Organization:

  • Session chair of the section "Network Analysis" in ISBRA 2020

Journal Reviewer:

  • BMC Bioinformatics
  • Frontiers in Molecular Biosciences
  • Scientific Reports
  • Frontiers in Genetics
  • PeerJ Computer Science
  • Journal of Computer Science and Technology

Membership:

  • IEEE Student Member, 2018-Now
  • CCF Student Member, 2018-Now
  • CAAI Student Member, 2018-Now

Honors and Awards

  • 2020, Outstanding Graduate, Central South University | 中南大学优秀毕业生
  • 2018, Outstanding student, Central South University | 中南大学优秀学生