个人简历

教育经历
2006年9月-2009年6月： 武汉大学，计算机学院，博士研究生
2007年9月-2008年8月： 新加坡国立大学，计算机学院，访问学生
2003年9月-2006年6月： 武汉大学，数学与统计学院，硕士研究生
1999年9月-2003年6月： 武汉大学，数学与统计学院，本科生
主要职历
2018年11月-至今：华中农业大学，信息学院，教授
2012年12月-2018年10月：武汉大学，计算机学院，副教授
2014年1月-2018年10月：武汉大学，计算机学院，珞珈青年学者
2015年2月-2016年2月：美国麻省医学院 访问学者
2009年9月-2012年11月：武汉大学，计算机学院，讲师

研究领域

数据挖掘，生物信息，人工智能，机器学习

近期论文

1. Wen Zhang*, Zhishuai Li, Wenzheng Guo, Weitai Yang, Feng Huang. A fast linear neighborhood similarity-based network link inference method to predict microRNA-disease associations. IEEE/ACM transactions on computational biology and bioinformatics, 29 July 2019, DOI: 10.1109/TCBB.2019.2931546.
2. Wen Zhang*, Kanghong Jing, Feng Huang, Yanlin Chen, Bolin Li, Jinghao Li, Jing Gong. SFLLN: A sparse feature learning ensemble method with linear neighborhood regularization for predicting drug-drug interactions. Information Sciences, September 2019, 497:189-201.
3. Wen Zhang*, Chenglin Yu, Xiaochan Wang, Feng Liu. Predicting CircRNA-disease Associations through Linear Neighborhood Label Propagation Method. IEEE Access, 2019, 10.1109/ACCESS.2019.2920942.
4. Wen Zhang*, Weiran Lin, Ding Zhang, Siman Wang, Jingwen Shi, Yanqing Niu. Recent advances in the machine learning-based drug-target interaction prediction. Current drug metabolism, 2019, 20(3):194-202(9).
5. Jiang Li, Yawen Xue, Muhammad Talal Amin, Yanbo Yang, Jiajun Yang, Wen Zhang, Wenqian Yang, Xiaohui Niu, Hong-Yu Zhang, Jing Gong*. ncRNA-eQTL: a database to systematically evaluate the effects of SNPs on non-coding RNA expression across cancer types. Nucleic acids research, 2019, gkz711
6. Yi-Cheng Gao, Xiong-Hui Zhou*, Wen Zhang*. An ensemble strategy to predict prognosis in ovarian cancer based on gene modules. Frontiers in genetics, 24 April 2019.
7. Wen Zhang*, Xiang Yue, Guifeng Tang, Wenjian Wu, Feng Huang, Xining Zhang. SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions. PLoS Computational Biology, December 2018, 14(12): e1006616.
8. Wen Zhang*, Xiaoting Lu, Weitai Yang, Feng Huang, Binlu Wang, Alan wang, and Qi Zhao. HNGRNMF: Heterogeneous Network-based Graph Regularized Nonnegative Matrix Factorization for predicting events of microbe-disease associations. 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018), Madrid, Spain, Dec 3-6, 2018.
9. Wen Zhang*, Guifeng Tang, Siman Wang, Yanlin Chen, Shuang Zhou, Xiaohong Li*. Sequence-derived linear neighborhood propagation method for predicting lncRNA-miRNA interactions. 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018), Madrid, Spain, Dec 3-6, 2018.
10. Wen Zhang*, Feng Huang, Xiang Yue, Xiaoting Lu, Weitai Yang, Zhishuai Li, Feng Liu. Prediction of Drug-Disease Associations and Their Effects by Signed Network-Based Nonnegative Matrix Factorization. 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018), Madrid, Spain, Dec 3-6, 2018.
11. Wen Zhang*, Xiang Yue, Weiran Lin, Wenjian Wu, Ruoqi Liu, Feng Huang, Feng Liu. Predicting drug-disease associations by using similarity constrained matrix factorization. BMC Bioinformatics, 2018, 19:233.
12. Wen Zhang*, Yanlin Chen, Dingfang Li, Xiang Yue. Manifold regularized matrix factorization for drug-drug interaction prediction. Journal of biomedical informatics, 2018, 88, 90-97
13. Wen Zhang*, Xiang Yue, Feng Huang, Ruoqi Liu, Yanlin Chen, Chunyang Ruan. Predicting drug-disease associations and their therapeutic function based on the drug-disease association bipartite network. Methods, 2018,145,51-59.
14. Wen Zhang*, Xinrui Liu, Yanlin Chen, Wenjian Wu, Wei Wang, Xiaohong Li. Feature-derived Graph Regularized Matrix Factorization for Predicting Drug Side Effects. February 2018, Neurocomputing 2018, 287:154-162
15. Wen Zhang*, Yanlin Chen, Dingfang Li. Drug-target interaction prediction through label propagation with linear neighborhood information. Molecules, 2017, 22(12), 2056
16. Wen Zhang*, Qianlong Qu, Yunqiu Qu, Yunqiu Zhang, Wei Wang. The linear neighborhood propagation method for predicting long non-coding RNA-protein interactions. Neurocomputing, 2018, 273(17):526-534
17. Wen Zhang*, Xiang Yue, Yanlin Chen, Weiran Lin, Bolin Li, Feng Liu, and Xiaohong Li. Predicting drug-disease associations based on the known association bipartite network. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2017), Kansan City, MO, USA, Nov 13 - Nov 16.
18. Wen Zhang*, Jingwen Shi, Guifeng Tang, Bolin Li, Weiran Lin, Xiang Yue, Yanlin Chen, and Dingfang Li. Predicting small RNAs in bacteria via sequence learning ensemble method. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2017), Kansan City, MO, USA, Nov 13 - Nov 16.
19. Wen Zhang*, Xiaopeng Zhu, Yu Fu, Junko Tsuji, Zhiping Weng. Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods. BMC bioinformatics, 2017, 18(Suppl 13):464.
20. Wen Zhang*, Xiang Yue, Feng Liu, Yanlin Chen, Shikui Tu, Qianlong Qu, Xining Zhang. A unified frame of predicting side effects of drugs by using linear neighborhood similarity. BMC Systems biology, 2017, 11(Suppl 6):101
21. Wen Zhang*, Yanlin Chen; Feng Liu, Fei Luo, Gang Tian, Xiaohong Li. Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data. BMC Bioinformatics, 2017, 18: 18.