Wen Zhang-College of Informatics

Name

Wen

Title

Zhang

Institute

College of Informatics, Huazhong Agricultural University

Address

No.1 Shizishan Street, Hongshan District, Wuhan 430070, China

Email

zhangwen@mail.hzau.edu.cn

Fax

Research Interest

· Graph learning algorithms and their applications in biomedical big data mining

· Recommender system algorithms and their applications in biomedical big data mining

· Deep learning algorithms and their applications in biomedical big data mining

· Ensemble learning algorithms and their applications in biomedical big data mining

· drug side effect prediction, drug-target interaction prediction, drug-drug interaction prediction, drug-disease association prediction

Academic activities

· China Computer Federation (CCF) Senior Member

· China Computer Federation (CCF) YOCSEF Wuhan Academic Member

· Committee Member, China Computer Federation, Technical Committee on Bioinformatics

· Standing Committee Member, Chinese Association for Artificial Intelligence, Technical Committee on Bioinformatics and Artificial life

· Reviewer for conferences “AAAI”, “BIBM” and journals “Bioinformatics”, “Briefings in Bioinformatics” “IEEE-ACM transactions on computational biology and bioinformatics” “Oncotarget”, “Molecular Therapy-Nucleic Acids”, “BMC Bioinformatics”, “Scientific Reports”, “PLOS ONE”, “Neurocomputing”, “Artificial Intelligence in Medicine” and “Journal of Biomedical Informatics”, “Applied Informatics”, “Neural Computing and Applications”.

Education and research experience

Work Experiences：

· 2018.11-present, College of Informatics, Huazhong Agricultural University, professor

· 2012.11-2018.10, School of Computer, Wuhan University, associate professor

· 2015.02-2016.02, University of Massachusetts Medical School, visiting scholar

· 2009.09-2012.11, School of Computer, Wuhan University, assistant professor

Education：

· 2006.09-2009.06, School of Computer, Wuhan University, Ph.D.

· 2007.09-2008.08, School of Computing, National university of Singapore, visiting Ph.D. student

· 2003.09-2006.06, School of Mathematics and Statistics, Wuhan University, Master

· 1999.09-2003.06, School of Mathematics and Statistics, Wuhan University, Bachelor

Grants (Government-funded)

· Big data-based machine learning methods for predicting adverse reaction of drugs. National Science Foundation of China (No.61772381), 2018.1-2021.12, Principal Investigator

· Data Integration and 3D dynamic pattern recognition from Multi-source Gene Expressions. National Science Foundation of China (No.61572368), 2016.1-2019.12, Principal Investigator

· Machine Learning Methods for predicting B-cell epitopes. National Science Foundation of China (No.61103126), 2012.1-2014.12, Principal Investigator

Representative publications（*for corresponding authors, # for first authors）

Homepage: http://zhangwenlab.cn/indexen.html

Google Scholar: https://scholar.google.com/citations?user=7gHmn88AAAAJ&hl=zh-CN

1. 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. (SCI, IF=9.101)

2. 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. (SCI, IF=4.531)

3. 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, 2020,36(4): 1241–1251 (SCI, IF=4.531)

4. 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 (SCI, IF= 4.428)

5. 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 (SCI, IF= 5.524)

6. 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, early access, (SCI, IF=2.896)

7. 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 (SCI, IF= 11.147)

8. Wen Zhang*, Guifeng Tang, Shuang Zhou, Yanqing Niu. LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination. BMC genomics, 2019, 20(11):1-12 (SCI, IF=3.501)

9. Yuchong Gong, Yanqing Niu, Wen Zhang*, Xiaohong Li. A network embedding-based multiple information integration method for the MiRNA-disease association prediction. BMC Bioinformatics 2019, 20(1):468 (SCI, IF=2.511)

10. 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(CCF B, regular paper, Best student paper nomination)

11. 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(CCF B, regular paper)

12. 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(CCF B, regular paper)

13. Yanzhen Xu, Xiaohan Zhao, Shuai Liu, Shichao Liu, Yanqing Niu, Wen Zhang*, Leyi Wei*. LncPred-IEL: A Long Non-coding RNA Prediction Method using Iterative Ensemble Learning. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), November 18-21, 2019, San Diego, CA, USA, pp: 555-562(CCF B, regular paper)

14. Shichao Liu, Ziyang Huang, Yang Qiu, Yi-Ping Phoebe Chen, Wen Zhang*. Structural Network Embedding using Multi-modal Deep Auto-encoders for Predicting Drug-drug Interactions. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), November 18-21, 2019, San Diego, CA, USA, pp: 445-450(CCF B, regular paper)

15. 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 (SCI, IF=2.277)

16. 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, regular paper)

17. 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, IF=2.511)

18. 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, IF= 2.95)

19. 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, IF=3.782)

20. 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, IF=4.072)

21. 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 (SCI, IF=4.072, ESI highly citation)

22. 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, regular paper)

23. 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, regular paper)

24. 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, IF=2.511)

25. 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 (SCI, IF=2.048)

26. 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, IF=2.511, ESI highly citation)