Associate Professor
Supervisor of Master's Candidates
Date of Employment:2020-09-09
School/Department:School of Computer Science and Engineering
Education Level:With Certificate of Graduation for Doctorate Study
Business Address:中南大学新校区信息大楼429
Contact Information:zengmin@csu.edu.cn
Degree:Doctoral Degree in Engineering
Alma Mater:中南大学
Discipline:Computer Science and Technology
曾敏，男，中南大学计算机学院副教授，硕士研究生导师。于2013年获得兰州大学电子信息科学与技术学士学位；2016年，2020年分别获得中南大学系统科学硕士学位和计算机科学与技术博士学位。主要研究方向是生物信息学（AI for Science），研究工作集中在利用和开发人工智能方法对生物信息学中的交叉前沿科学问题进行探索和研究，具体研究内容包括生物序列分析、疾病相关预测、医学大数据分析等，目前在Bioinformatics、Briefings in Bioinformatics、IJCAI等国际期刊和会议上发表学术论文50余篇，据Google Scholar统计显示总引用1500余次。担任BMC Bioinformatics的编委，Frontiers in Genetics的客座编辑，CCF-B类推荐会议BIBM、CCF-C类推荐会议APBC、ISBRA的程序委员会成员，担任Bioinformatics、Briefings in Bioinformatics等多个期刊审稿人。主持国家自然科学基金青年项目1项，国家重点研发计划子课题1项，湖南省自然科学基金青年项目1项。参与国家重点研发计划、国家自然科学基金重点项目、国家自然科学基金面上项目等科研项目多项。
【硕士招生】
每年招收3名左右硕士研究生，欢迎对人工智能、机器学习、深度学习、生物信息学感兴趣的同学与我联系，课题组会为每一位学生提供良好的科研条件和生活补助。（邮箱：zengmin@csu.edu.cn）
代表性论文（发表论文完整列表，请见我的Google Scholar页面）
[1] 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]
[2] Min Zeng, Yifan Wu, Yiming Li, Rui Yin, Chengqian Lu, Junwen Duan, and Min Li*. LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism. Bioinformatics, 39 (12), btad752, 2023. [PDF] [Code]
[3] Min Zeng, Yifan Wu, Chengqian Lu, Fuhao Zhang, Fang-Xiang Wu, Min Li*. DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding. Briefings in Bioinformatics, 23 (1), bbab360, 2022. [PDF] [Code]
[4] Min Li, Baoying Zhao, Rui Yin, Chengqian Lu, Fei Guo, Min Zeng*. GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation. Briefings in Bioinformatics. 24 (1), bbac565, 2022. [PDF] [Code]
[5] 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, 18 (1), 296-305, 2021. [PDF] [Code]
