章文

姓名

章文

性别


职称

教授

学位

博士

电话


邮箱

zhangwen@mail.hzau.edu.cn

zhangwen@whu.edu.cn

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

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

科研成果

具体内容详见个人主页: http://zhangwenlab.cn

章文老师是中国计算机学会(CCF)高级会员,CCF YOCSEF武汉副主席,中国人工智能学会生物信息学与人工生命专委会常务委员,中国计算机学会生物信息学专委会委员,计算机学会计算机应用专委会委员。
章文老师长期从事人工智能算法及其在生物医学大数据分析方面的研究,在Information Sciences, PLOS Computational Biology, Bioinformatics, Briefings in Bioinformatics, IEEE-ACM Transactions on Computational Biology and Bioinformatics, BMC Bioinformatics, Neurocomputing 等杂志和中国计算机学会推荐的国际会议上发表论文60余篇, 含多篇计算机ESI高被引论文。 担任多个中国计算机学会推荐国际会议程序委员会委员,包括BIBM,GIW,AAAI,APWeb-WAIM,UIC等。担任多个重要期刊的审稿人,包括Neural networks, Bioinformatics, Briefings in Bioinformatics, Molecular Therapy-Nucleic Acids, BMC Bioinformatics, Neurocomputing等。先后主持/完成国家自然科学基金青年项目(1项)、面上项目(2项)和多个省部级科研项目。

招收计算机、数学、或者生物信息学背景的博士生研究生,硕士研究生,博士后;欢迎相关本科生参与科研。感兴趣的同学欢迎邮件联系,署名邮件必回复。

实验室研究方向:

知识图谱算法及其应用

图神经网络算法及其应用

推荐系统算法及其应用

集成学习算法及其应用

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。

查看毕业学生去向

查看云树本科生指导情况

近三年代表论文

(具体论文列表:full publication list at My Google Scholar  My ORCID  My Publons Profile )

1. Zhouxin Yu#,Feng Huang#, Xiaohan Zhao, Wenjie Xiao, Wen Zhang*.Predicting Drug-Disease Associations through Layer Attention Graph Convolutional Network. Briefings in Bioinformatics, 1 September 2020, doi:10.1093/bib/bbaa243.

2. Xiangan Chen, Shuai Liu, Wen Zhang*. Predicting Coding Potential of RNASequences by Solving Local Data Imbalance. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2 September 2020, doi:10.1109/TCBB.2020.3021800.

3. Feng Huang#, Xiang Yue#, Zhankun Xiong, Zhouxing Yu,Shichao Liu, Wen Zhang*. Tensor Decomposition with Relational Constraints for Predicting Multiple Types of MicroRNA-disease Associations. Briefings in Bioinformatics, 6 June 2020,doi:10.1093/bib/bbaa140.

4. Yifan Deng, Xinran Xu, Yang Qiu, Jingbo Xia, Wen Zhang*, Shichao Liu*. A multimodal deep learning framework for predicting drug-drug interaction events. Bioinformatics, 14 May 2020, doi:10.1093/bioinformatics/btaa501.

5. Xiang Yue*, Zhen Wang, Jingong Huang, Srinivasan Parthasarathy, Soheil Moosavinasab, Yungui Huang, Simon M Lin, Wen Zhang, Ping Zhang, Huan Sun*. Graph embedding on biomedical networks: methods, applications and evaluations. Bioinformatics, 15 Feb 2020, 36 (4):1241-1251.(计算机 ESI高被引)

6. 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, 2020, 48 (D1):D956-D963

7. Xiaochan Wang, Yuchong Gong, Jing Yi, Wen Zhang*. Predicting gene-disease associations from the heterogeneous network using graph embedding. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), November 18-21, 2019, San Diego, CA, USA, pp:504-511(Best student paper nomination)

8. Shuang Zhou, Xiang Yue, Xinran Xu, Shichao Liu, Wen Zhang*, Yanqing Niu*. LncRNA-miRNA interaction prediction from the heterogeneous network through graph embedding ensemble learning. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), November 18-21, 2019, San Diego, CA, USA, pp: 622-627

9. Zeming Liu, Feng Liu*, Chengzhi Hong, Meng Gao, Yi-Ping Phoebe Chen, Shichao Liu, Wen Zhang*. Detection of Cell Types from Single-cell RNA-seq Data using Similarity via Kernel Preserving Learning Embedding. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), November 18-21, 2019, San Diego, CA, USA, pp: 451-457

10. 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.

11. 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.(计算机 ESI高被引)

12. 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.

13. 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).

14. 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.

15. 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.

16. 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.

17. 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.

18. 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.

19. 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.

20. 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

21. 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.

22. 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

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

24. 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(计算机 ESI高被引)

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