工学博士，硕士生导师

湖南大学计算机科学与技术专业博士，讲师，硕士生导师。长期从事生物信息学、癌症驱动基因与驱动突变发现、数据挖掘等方面的研究，主持国家自然科学基金项目、湖南省自然科学基金等国家/省部级科研项目4项，以第一/通讯作者发表SCI论文12篇。指导学生参加各类学科竞赛，获国家级奖项2项，省级奖项3项。

教育经历：

2015-2019：湖南大学，计算机科学与技术，博士；

2010-2013：湖南大学，计算机科学与技术，硕士；

2006-2010：昆明理工大学，计算机科学与技术，本科。

工作经历：

2019-至今：长沙学院计算机科学与工程学院，软件工程系，讲师

主讲课程：

《计算机组成原理》，《数据仓库与联机分析》，《计算机系统》，《音频处理技术》。

科研项目：

1.面向癌症亚型特异性的进程模型研究，国家自然科学基金青年项目：62302061，2024.1-2026.12，在研，主持

2.面向多组学数据的癌症特异性模块识别方法研究，湖南省教育厅优秀青年项目：20B059，2020.1-2022.12，已结题，主持

3.面向亚型特异性的癌症进程模型研究，湖南省自然科学基金项目：2023JJ40080 ，2022.1-2024.12，在研，主持

4.基于横截面组学数据的癌症亚型特异性进程模型研究，长沙市自然科学基金项目：KQ2208431，2022.1-2024.12，在研，主持

主要论文：

[1]     Zhang W, Wang S L. An integrated framework for identifying mutated driver pathway and cancer progression[J]. IEEE/ACM transactions on computational biology and bioinformatics, 2017, 16(2): 455-464.

[2]     Zhang W, Wang S L. An efficient strategy for identifying cancer-related key genes based on graph entropy[J]. Computational biology and chemistry, 2018, 74: 142-148.

[3]     Zhang W, Wang S L. A Novel Method for Identifying the Potential Cancer Driver Genes Based on Molecular Data Integration[J]. Biochemical genetics, 2020, 58: 16-39.

[4]     Zhang W, Zeng Y, Wang L, Liu Y, Cheng Y. An Effective Graph Clustering Method to Identify Cancer Driver Modules[J]. Frontiers in Bioengineering and biotechnology, 2020, 8(271).

[5]     Zhang W, Wang S L, Liu Y. Identification of Cancer Driver Modules Based on Graph Clustering from Multi-omics Data[J]. Journal of Computational Biology, 2021, 28(10).

[6]     Zhang, W.; Xiang, X.; Zhao, B.; Huang, J.; Yang, L.; Zeng, Y. Identifying Cancer Driver Pathways Based on the Mouth Brooding Fish Algorithm. Entropy 2023, 25, 841. https://doi.org/10.3390/e25060841

[7]     Zhang W, Zeng Y, Xiang X, Zhao B, Hu S, Li L, Zhu X and Wang L (2025) Association prediction of lncRNAs and diseases using multiview graph convolution neural network. Front. Genet. 16:1568270. doi: 10.3389/fgene.2025.1568270

[8]     Wei Zhang, Yifu Zeng, Bihai Zhao, Jie Xiong, Tuanfei Zhu, Jingjing Wang, Guiji Li, Lei Wang, An Effective Method to Identify Cooperation Driver Gene Sets, Current Bioinformatics; Volume 20, Issue 1, Year 2025, e040424228643.

[9]     Pei C, Wang S L, Fang J, Zhang W. GSMC: Combining parallel Gibbs sampling with maximal cliques for hunting DNA motif[J]. Journal of Computational Biology, 2017, 24(12): 1243-1253.

[10]  Luo D, Wang S L, Fang J, Zhang W. MIMPFC: Identifying miRNA–mRNA regulatory modules by combining phase-only correlation and improved rough-fuzzy clustering[J]. Journal of bioinformatics and computational biology, 2018, 16(01): 522-531.

[11]  Mao G, Wang S L, Zhang W. Prediction of Potential Associations Between MicroRNA and Disease Based on Bayesian Probabilistic Matrix Factorization Model[J]. Journal of Computational Biology, 2019, 26(9):1030-1039.

[12]  Liu Y, Wang S L, Zhang J, Zhang W, Zhou S, Li W. DMFMDA: Prediction of microbe-disease associations based on deep matrix factorization using Bayesian Personalized Ranking[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020.

[13]  Liu Y, Wang S L, Zhang J F, Zhang W, Li W. A neural collaborative filtering method for identifying miRNA-disease associations[J]. Neurocomputing, 2021, 422: 176-185.

[14]  Liu Y, Wang S L, Zhang J F, Zeng X, Zhang W. Are dropout imputation methods for scRNA-seq effective for scATAC-seq data? [J]. Briefings in Bioinformatics, 2022, 23(1)

[15]  Liu Y, Wang S L, Zhang J F, Zeng X, Zhang W et al. A heterogeneous graph cross-omics attention model for single-cell representation learning[C]. The IEEE International Conference on Bioinformatics and Biomedicine (BIBM) conference, 2022.

招生信息：

欢迎对癌症基因组学、数据挖掘、生物信息学等感兴趣的学生报考硕士研究生。本课题组致力于前沿交叉学科算法研究与实际应用开发，特别欢迎那些具有浓厚研究兴趣、勤奋踏实、愿意投入时间精力深入学术探索的同学加入。我们注重培养学生的科研能力和创新思维，为表现优秀的学生提供与研究工作匹配的劳务补贴。真诚期待与热爱科研、愿意挑战自我的你共同成长！

联系方式：zhangwei6409520@hnu.edu.cn

办公地址：长沙学院计算机科学与工程学院1604