• 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]

• 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]

• 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.

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