华中农业大学信息学院大数据科学系研究生导师介绍如下：

章文，男，博士，华中农业大学 信息学院 教授 博士生导师

邮箱：zhangwen@mail.hzau.edu.cn

zhangwen@whu.edu.cn(使用中)

工作单位：华中农业大学信息学院

研究方向：数据挖掘，生物信息，人工智能，机器学习

教育经历

2015.2-2016.2 美国麻省医学院 访问学者

2006.9-2009.6 武汉大学计算机学院、新加坡国立大学联合培养 博士

2003.9-2006.6 武汉大学数学与统计学院 硕士

1999.9-2003.6 武汉大学数学与统计学院 本科

主要职历

2018.11-至今 华中农业大学 信息学院 教授 博士生导师

2012.12-2018.10 武汉大学计算机学院 副教授 珞珈青年学者

2009-2012.11 武汉大学计算机学院 讲师

科研成果

在生物信息学、数据挖掘的交叉领域，发表论文50余篇，含多篇计算机ESI高被引论文。担任国内多个学会的专业委员会委员，包括：中国人工智能学会生物信息学与人工生命专业委员会、中国计算机学会生物信息学专业委员会、中国生物信息学学会生物医学数据挖掘与计算专业委员会等。担任多个CCF推荐国际会议程序委员会委员，包括：BIBM，GIW，AAAI，APWeb-WAIM，UIC，ICIC。 担任十多种高影响因子期刊审稿人。主持国家自然科学基金青年项目、面上项目和多个省部级科研项目。

实验室简介：面向生物医学数据，研究矩阵分解、表达学习、图学习，网络缺失边预测等数据挖掘方法、机器学习模型，探索药物副作用、药物靶点、药物-药物反应、药物-疾病关系、微生物-疾病关系、脑科学与人工智能等科学问题，发现具有价值的知识和信息。

2019年开始在信息学院招生，欢迎硕士研究生、博士研究生、博士后和本科生加入课题组。有意者，请通过邮件联系。

学生要求：

1 计算机、数学或者生物信息学背景。

2 有一定编程基础，python 或者 matlab，或者能够自学掌握。

3 对于科学研究有比较浓厚的兴趣，刻苦努力。

武汉大学指导学生和科研情况点击http://www.bioinfotech.cn

1. 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. (数学与计算生物学领域SCI一区，CCF B类)

2. 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. (CCF B类会议)

3. 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. (CCF B类会议)

4. 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. (CCF B类会议)

5. 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. (SCI三区, CCF C类)

6. 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 (SCI三区)

7. Wen Zhang*, Weiran Lin, Ding Zhang, Siman Wang, Jingwen Shi, Yanqing Niu. Recent advances in the machine learning-based drug-target interaction prediction. 2018, Current drug metabolism (in press, SCI三区)

8. 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. (SCI二区)

9. 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 (SCI二区, CCF C类)

10. Wen Zhang*, Yanlin Chen, Dingfang Li. Drug-target interaction prediction through label propagation with linear neighborhood information. Molecules, 2017, 22(12):2056 (SCI三区)

11. 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, 273:526-534 (SCI二区, CCF C类，计算机类ESI高被引论文)

12. 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 (CCF B类会议)

13. 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 (CCF B类会议)

14. 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 (SCI三区, CCF C类)

15. 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(S6) (SCI三区)

16. Wen Zhang*, Yanlin Chen, Shikui Tu, Feng Liu, and Qianlong Qu..Drug side effect prediction through linear neighborhoods and multiple data source integration. 2016 IEEE International Conference on Bioinformatics and Biomedicine(BIBM 2016), ShenZhen, China, Dec 15-18, 2016. (CCF B类会议)

17. Wen Zhang*, Xiaopeng Zhu, Yu Fu, Junko Tsuji, and Zhiping Weng.The prediction of human splicing branchpoints by multi-label learning. 2016 IEEE International Conference on Bioinformatics and Biomedicine(BIBM 2016), ShenZhen, China, Dec 15-18, 2016. (CCF B类会议)

18. 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(SCI三区, CCF C类，计算机类ESI高被引论文)

19. Dingfang Li, Longqiang Luo, Wen Zhang*., Feng Liu, Fei Luo. A genetic algorithm-based weighted ensemble method for predicting transposon-derived piRNAs. BMC Bioinformatics (2016) 17: 329. (SCI三区, CCF C类)

20. Longqiang Luo, Dingfang Li, Wen Zhang*, Shikui Tu, Xiaopeng Zhu, and Gang Tian. Accurate Prediction of Transposon-Derived piRNAs by Integrating Various Sequential and Physicochemical Features. PLoS One.2016, 11(4):e0153268. (SCI三区)

21. Ruichu Cai, Zhenjie Zhang,Srinivasan Parthasarathy, Anthony K. H. Tung, Zhifeng Hao, Wen Zhang, Multi-Domain Manifold Learning for Drug-Target Interaction Prediction. SIAM International Conference on Data Mining (SDM16), June 2016. DOI: 10.1137/1.9781611974348.3 (CCF B类会议)

22. Wen Zhang*, Feng Liu, Longqiang Luo, Jingxia Zhang, Predicting drug side effects by multi-label learning and ensemble learning. BMC Bioinformatics. 2015, 16:365 (SCI三区, CCF C类)

23. Wen Zhang*, Hua Zou, Longqiang Luo, Qianchao Liu, Weijian Wu, and Wenyi Xiao. Predicting potential side effects of drugs by recommender methods and ensemble learning. Neurocomputing, 2015, 173(3):979–987. (SCI二区, CCF C类)

24. Wen Zhang, Yanqing Niu, Hua Zou, Longqiang Luo, Qianchao Liu, Weijian Wu. Accurate prediction of immunogenic T-cell epitopes from epitope sequences using the genetic algorithm-based ensemble learning. PLoS One 2015 28;10(5):e0128194. (SCI三区)

25. Wen Zhang, Yanqing Niu, Yi Xiong, Meng Ke. Prediction of conformational B cell epitopes(专著邀请章节). “Immunoinformatics”, (Series Editor: John Walker), 2014. (专著, Springer出版，第二版). Springer, pp 185-196, New York, 2014/6/27

26. Juan Liu, Wen Zhang. Databases for B cell epitopes(专著邀请章节). An invited Chapter in the second edition of the book titled “Immunoinformatics”, under the series titled “Methods in Molecular Biology” (Series Editor: John Walker). (专著, Springer出版，第二版) .Springer, pp 135-148, New York, 2014/6/27

27. Wen Zhang*, Juan Liu, Yi Xiong, Meng Ke, and Ke Zhang. Predicting immunogenic T-cell epitopes by combining various sequence-derived features. The IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2013). 18-21 Dec. 2013, Page(s):4-9, Shanghai, China, Dec 2013. (CCF B类会议)

28. Wen Zhang*, Yanqing Niu, Yi Xiong, Meng Zhao, Rongwei Yu, Juan Liu. Computational prediction of conformational B-cell epitopes from antigen primary structures by ensemble learning. PLOS One, 7(8): e43575,2012年8月(SCI三区)

29. Wen Zhang*, Juan Liu, Meng Zhao, Qingjiao Li. Predicting linear B-cell epitopes by using sequence-derived structural and physicochemical features. International Journal of Data Mining and Bioinformatics, 6 (5): 557-569, 2012年9月(SCI四区)

30. Yi Xiong, Juan Liu, Wen Zhang, Tao Zeng. Prediction of heme binding residues from protein sequences with integrative sequence profiles. Proteome Science(Suppl 1): S20, 2012年6月(SCI三区)

31. Yi Xiong, X Junfeng Xia, Wen Zhang, Juan Liu. Exploiting a reduced set of weighted average features to improve prediction of DNA-binding residues from 3D Structures. 2011, PLOS One, 6:e28440, (SCI三区)

32. Wen Zhang*, Yi Xiong, Meng Zhao, Hua Zou, Xinghuo Ye, Juan Liu. Prediction of conformational B-cell epitopes from 3D structures by random forest with a distance-based feature. BMC Bioinformatics, 12:341, 2011年8月(SCI三区)

33. Wen Zhang*, Juan Liu, Yanqing Niu. Quantitative prediction of MHC-II binding affinity using particle swarm optimization. Artificial intelligence in medicine, 50(2): 127-132, 2010年10月, (SCI三区)

34. Wen Zhang*, Juan Liu, Yanqing Niu. Quantitative prediction of MHC-II peptide binding affinity using relevance vector machine. Applied Intelligence,31(2): 180-187,2009年9月, (SCI三区)

35. Wen Zhang*, Juan Liu, Yanqing Niu, Lian Wang, Xihao Hu. A Bayesian regression approach to the prediction of MHC-II binding affinity. Computer Methods and Programs in Biomedicine, 92(1):1-7,2008年6月, (SCI三区)