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博士。华中师范大学数学与统计学学院教授,博士研究生导师。主要研究生物医学数据挖掘的数学建模与机器学习方法。现主持国家自然科学基金面上项目1项、湖北省自然科学基金面上项目1项, 华中师范大学中央高校基本科研业务费-探索创新项目1项。曾主持国家自然科学基金青年项目1项,参与国家重点研发计划“精准医学研究”重点专项1项,参与国家自然科学基金重点项目1项。已在Bioinformatics、 IEEE transactions on Cybernetics、 IEEE Transactions on Image Processing、BMC Bioinformatics、BMC Genomics、IEEE/ACM Transactions on Computational Biology and Bioinformatics等重要学术期刊发表学术论文40余篇,累计影响因子200左右。论文被累计引用700余次(谷歌学术)。更多信息可参考谷歌学术主页:https://scholar.google.com/citations?user=mGTGvmUAAAAJ&hl=en,或researchgate主页https://www.researchgate.net/profile/Zhang_Xiao-Fei 开设课程 时间序列分析、数据挖掘 教育经历 2008.9 - 2013.6 中山大学, 应用数学, 博士 2004.9 - 2008.6 华中师范大学, 信息与计算科学, 本科 工作经历 2019.7 - 现在 华中师范大学, 教授 2017.7 - 2019.6 华中师范大学, 副教授 2016.1 - 2017.1 香港城市大学, 高级研究助理 2013.7 - 2017.6 华中师范大学, 讲师 2013.1 - 2013.7 香港城市大学, 研究助理 研究成果 论文涉及的代码及软件可以从以下网址获取:https://github.com/Zhangxf-ccnu 承担项目: 6. 国家自然科学基金面上项目,11871026,基于稀疏概率图模型的多癌症多组学生物网络构建方法研究,2019/01-2021/12,53万元 5. 湖北省自然科学基金面上项目,2018CFB521,跨癌症类型的肿瘤网络标志物识别算法研究,2018年1月 -2019年12月,5万元 4. 中央高校基本科研业务费-探索创新项目,跨癌症类型的差异表达因子识别算法研究,2018年1月-2019年12月,10万元 3. 国家自然科学基金青年科学基金项目,61402190,基于多视角蛋白质相互作用网络的多层次生物标志物检测,2015/01-2017/12,24万元,已结题 2. 中央高校基本科研业务费-青年教师项目,基于随机图模型的蛋白质功能模块探测研究,2015年1月-2016年12月,4万元,已结题 1. 中山大学博士研究生创新人才培养资助项目,基于图模型的蛋白质相互作用网络的结构及功能研究,2012/9 - 2013/6,经费2万元,已结题 参与项目: 5. 2018.01 - 2020.12 基于临床生物信息学研发慢性阻塞性肺病的个体化治疗靶标和新技术, 国家重点研发计划“精准医学研究”重点专项,SQ2017YFSF090207,经费948万元 4. 2016.01 - 2020.12 高通量微生物组学数据模式提取及分析,国家自然科学基金-重点项目,61532008,经费290万元 3. 2014.01 – 2017.12 基于蛋白质相互作用网络的复杂疾病分子机理研究61375033, 面上项目,经费79万元 2. 2013.10 – 2016.10 广东省重点项目,经费32万元 1. 2013.01 – 2015.12 基于稀疏随机图模型的蛋白质相互作用网络分析,教育部高等学校博士点科研基金项目20120171110016,经费12万元 研究生(硕士、博士)招生: 招生专业:应用统计、数理统计 其他要求: a) 数学分析,线性代数,数值分析,概率论与数理统计,多元统计,统计推断,最优化等课程基础扎实。 b) 至少精通两门程序语言:R, Matlab, Python, C++, Java。 c) 英语的听、说、读、写能力强,需要较强的科研论文阅读与写作能力,一般要求英语六级500分以上。 d) 对研究方向感兴趣、对科学研究有热情、不怕吃苦、不怕失败、做事认真负责。混学位者请勿联系。 培养学生获奖情况 (2)2019年研究生国家奖学金:涂佳娟(博士)、袁瑞(硕士)、王蒙国(硕士) (1)2018年研究生国家奖学金:许婷(硕士)

研究领域

数据挖掘、机器学习、生物信息学

近期论文

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[10] Le Ou-Yang, Dehan Cai, Xiao-Fei Zhang*, Hong Yan, WDNE: an integrative graphical model for inferring differential networks from multi-platform gene expression data with missing values, Briefings in Bioinformatics, 2021, 10.1093/bib/bbab086. [9] Zi-Chao Zhang#, Xiao-Fei Zhang#, Min Wu, Le Ou-Yang*, Xing-Ming Zhao, Xiao-Li Li, A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks, Bioinformatics, 2020, 36(11), 3474–3481. [8] Ke Jin, Le Ou-Yang, Xing-Ming Zhao, Hong Yan, Xiao-Fei Zhang*, scTSSR: gene expression recovery for single-cell RNA sequencing using two-side sparse self-representation, Bioinformatics, 2020, 36(10), 3131–3138. [7] Jia-Juan Tu, Le Ou-Yang, Hong Yan, Xiao-Fei Zhang*, Hong Qin*, Joint reconstruction of multiple gene networks by simultaneously capturing inter-tumor and intra-tumor heterogeneity,Bioinformatics, 2020, 36(9), 2755–2762. [6] Xiao-Fei Zhang, Le Ou-Yang*, Ting Yan, Xiaohua Hu, Hong Yan, A joint graphical model for inferring gene networks across multiple subpopulations and data types,IEEE Transactions on Cybernetics, 2019, DOI: 10.1109/TCYB.2019.2952711. [5] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xing-Ming Zhao, Xiaohua Hu, Hong Yan, EnImpute: imputing dropout events in single cell RNA sequencing data via ensemble learning, Bioinformatics, 2019, 35(22), 4827–4829. [4] Le Ou-Yang, Xiao-Fei Zhang*, Xing-Ming Zhao, Debby D Wang, Fu Lee Wang, Baiying Lei, Hong Yan, Joint learning of multiple differential networks with latent variables, IEEE Transactions on Cybernetics, 2019, 49(9): 3494 - 3506. [3] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xiaohua Hu, Hong Yan, DiffNetFDR: differential network analysis with false discovery rate control, Bioinformatics, 2019, 35(17), 3184–3186. [2] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xiaohua Hu, Hong Yan, DiffGraph: an R package for identifying gene network rewiring using differential graphical models, Bioinformatics, 2018,34(9): 1571-1573. [1] Xiao-Fei Zhang#, Le Ou-Yang#*, Hong Yan, Incorporating prior information into differential network analysis using non-paranormal graphical models, Bioinformatics, 2017, 33(16): 2436–2445. 2021 [1] Xiao-Fei Zhang, Le Ou-Yang*, Ting Yan, Xiaohua Hu, Hong Yan, A joint graphical model for inferring gene networks across multiple subpopulations and data types,IEEE Transactions on Cybernetics, 2021, 51(2): 1043 - 1055 [2] Le Ou-Yang, Dehan Ca, Xiao-Fei Zhang*, Hong Yan, WDNE: an integrative graphical model for inferring differential networks from multi-platform gene expression data with missing values, Briefings in Bioinformatics, 2021, 10.1093/bib/bbab086. 2020年 [1] Ke Jin, Le Ou-Yang, Xing-Ming Zhao, Hong Yan, Xiao-Fei Zhang*, scTSSR: gene expression recovery for single-cell RNA sequencing using two-side sparse self-representation, Bioinformatics, 2020, 36(10), 3131–3138. [2] Jia-Juan Tu, Le Ou-Yang, Hong Yan, Xiao-Fei Zhang*, Hong Qin*, Joint reconstruction of multiple gene networks by simultaneously capturing inter-tumor and intra-tumor heterogeneity,Bioinformatics, 2020, 36(9), 2755–2762. [3] Zi-Chao Zhang#, Xiao-Fei Zhang#, Min Wu, Le Ou-Yang*, Xing-Ming Zhao, Xiao-Li Li, A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks, Bioinformatics, 2020, 36(11), 3474–3481. [4] Le Ou-Yang, Xiao-Fei Zhang*, Hong Yan, Sparse regularized low-rank tensor regression with applications in genomic data analysis, Pattern Recognition, 2020, 107, 107516. [5] Le Ou-Yang, Xiao-Fei Zhang*, Xiaohua Hu, Hong Yan, Differential network analysis via weighted fused conditional Gaussian graphical model, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, 17(6): 2162 - 2169 [6] Rui Yuan, Le Ou-Yang, Xiaohua Hu, Xiao-Fei Zhang*, Identifying gene network rewiring using robust differential graphical model with multivariate t-distribution, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, 17(2): 712 - 718 [7] Yu-Ting Tan, Le Ou-Yang, Xingpeng Jiang, Hong Yan, Xiao-Fei Zhang*, Identifying gene network rewiring based on partial correlation, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, DOI: 10.1109/TCBB.2020.3002906. 2019年 [1] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xing-Ming Zhao, Xiaohua Hu, Hong Yan, EnImpute: imputing dropout events in single cell RNA sequencing data via ensemble learning, Bioinformatics, 2019, 35(22), 4827–4829. [2] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xiaohua Hu, Hong Yan, DiffNetFDR: Differential network analysis with false discovery rate control, Bioinformatics, 2019, 35(17), 3184–3186. [3] Le Ou-Yang, Xiao-Fei Zhang*, Xing-Ming Zhao, Debby D Wang, Fu Lee Wang, Baiying Lei, Hong Yan, Joint learning of multiple differential networks with latent variables, IEEE Transactions on Cybernetics, 2019, 49(9): 3494 - 3506. [4] Jia-Juan Tu, Le Ou-Yang, Xiaohua Hu, Xiao-Fei Zhang*, Identifying gene network rewiring by combining gene expression and gene mutation data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019, 16(3): 1042 - 1048. [5] Nuosi Wu, Jiang Huang, Xiao-Fei Zhang, Le Ou-Yang*, Shan He, Zexuan Zhu, Weixin Xie, Weighted fused pathway graphical lasso for joint estimation of multiple gene networks, Frontiers in Genetics, 2019, 10: 623. [6] Le Ou-Yang, Jiang Huang, Xiao-Fei Zhang, Yan-Ran Li, Yiwen Sun, Shan He, Zexuan Zhu, LncRNA-Disease Association Prediction using Two-Side Sparse Self-Representation, Frontiers in Genetics, 2019, 10: 476 [7] Ting Xu, Le Ou-Yang, Hong Yan, Xiao-Fei Zhang*, Time-varying differential network analysis for revealing network rewiring over cancer progression, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019, DOI: 10.1109/TCBB.2019.2949039. 2018年 [1] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xiaohua Hu, Hong Yan, DiffGraph: An R package for identifying gene network rewiring using differential graphical models, Bioinformatics, 2018,34(9): 1571-1573. [2] Ting Xu, Le Ou-Yang, Xiaohua Hu, Xiao-Fei Zhang*, Identifying gene network rewiring by integrating gene expression and gene network data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018, 15(6): 2079-2085. 2017年 [1] Xiao-Fei Zhang#, Le Ou-Yang#*, Hong Yan, Incorporating prior information into differential network analysis using non-paranormal graphical models, Bioinformatics, 2017, 33(16): 2436–2445. [2] Xiao-Fei Zhang, Le Ou-Yang*, Hong Yan, Node-based differential network analysis in genomics, Computational Biology and Chemistry, 2017, 69: 194-201. [3] Le Ou-Yang, Hong Yan, Xiao-Fei Zhang*, A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks, BMC Bioinformatics, 2017, 8(Suppl 13):46. [4] Le Ou-Yang, Xiao-Fei Zhang*, Min Wu, Xiao-Li Li, Node-based learning of differential networks from multi-platform gene expression data, Methods, 2017, 129:41-49. [5] Le Ou-Yang, Hong Yan, Xiao-Fei Zhang*, Identifying differential networks based on multi-platform gene expression data, Molecular Biosystems, 2017, 13(1):183~192. 2016年 [1] Xiao-Fei Zhang#, Le Ou-Yang#*, Xing-Ming Zhao, Hong Yan, Differential network analysis from cross-platform gene expression data, Scientific Reports, 2016, 6: 34112. [2] Le Ou-Yang, Xiao-Fei Zhang#, Dao-Qing Dai*, Meng-Yun Wu, Yuan Zhu, Zhiyong Liu, Hong Yan, Protein complex detection based on partially shared multi-view clustering, BMC Bioinformatics, 2016, 17:371. [3] Xiao-Fei Zhang, Le Ou-Yang, Dao-Qing Dai*, Meng-Yun Wu, Yuan Zhu, Hong Yan, Comparative analysis of housekeeping and tissue-specific driver nodes in human protein interaction networks, BMC Bioinformatics, 2016, 17:358. [4] Meng-Yun Wu, Xiao-Fei Zhang#, Dao-Qing Dai*, Le Ou-Yang, Yuan Zhu, Hong Yan, Regularized logistic regression with network-based pairwise interaction for biomarker identification in breast cancer, BMC Bioinformatics, 2016, 17:108. [5] Le Ou-Yang, Min Wu, Xiao-Fei Zhang, Dao-Qing Dai*, Xiao-Li Li*, Hong Yan, A two-layer integration framework for protein complex detection, BMC Bioinformatics, 2016.2.24, 17:100. 2015年 [1] Xiao-Fei Zhang, Le Ou-Yang, Xiaohua Hu, Dao-Qing Dai*, Identifying binary protein-protein interactions from affinity purification mass spectrometry data, BMC Genomics, 2015, 16: 745. [2] Xiao-Fei Zhang, Le Ou-Yang, Yuan Zhu, Meng-Yun Wu, Dao-Qing Dai*, Determining minimum set of driver nodes in protein-protein interaction networks, BMC Bioinformatics, 2015, 16: 146. [3] Le Ou-Yang, Dao-Qing Dai*, Xiao-Fei Zhang, Detecting protein complexes from signed protein-protein interaction networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015, 12(6):1333~1344. 2014年 [1] Xiao-Fei Zhang, Dao-Qing Dai*, Le Ou-Yang, Hong Yan, Detecting overlapping protein complexes based on a generative model with functional and topological properties, BMC Bioinformatics, 2014, 15: 186. [2] Le Ou-Yang, Dao-Qing Dai*, Xiao-Li Li*, Min Wu, Xiao-Fei Zhang, Peng Yang, Detecting temporal protein complexes from dynamic protein-protein interaction networks, BMC Bioinformatics, 2014, 15:335. 2013年 [1] Meng-Yun Wu, Dao-Qing Dai*, Xiao-Fei Zhang, Yuan Zhu, Cancer subtype discovery and biomarker identification via a new robust network clustering algorithm, PLos One, 2013, 8(6):e66256. [2] Le Ou-Yang, Dao-Qing Dai*, Xiao-Fei Zhang, Protein complex detection via weighted ensemble custering based on Bayesian nonnegative matrix factorization, PLos One, 2013, 8(5):e62158. [3] Xiao-Xin Li, Dao-Qing Dai*, Xiao-Fei Zhang, Chuan-Xian Ren, Structured sparse error coding for face recognition with occlusion, IEEE Transactions on Image Processing, 2013, 22(5):1889~1900. [4] Yuan Zhu, Xiao-Fei Zhang, Dao-Qing Dai*, Meng-Yun Wu, Identifying spurious interactions and predicting missing interactions in the protein-protein interaction networks via a generative network model, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2013, 10(1):219~225. 2012年 [1] Xiao-Fei Zhang, Dao-Qing Dai*, Xiao-Xin Li, Protein complexes discovery based on protein-protein interaction data via a regularized sparse generative network model, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2012, 9(3): 857~870. [2] Xiao-Fei Zhang, Dao-Qing Dai*, A framework for incorporating functional interrelationships into protein function prediction algorithms, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2012, 9(3): 740~753. [3] Xiao-Fei Zhang, Dao-Qing Dai*, Le Ou-Yang, Meng-Yun Wu, Exploring overlapping functional units with various structure in protein interaction networks, Plos One, 2012.8.20, 7(8): e43092. [4] Meng-Yun Wu, Dao-Qing Dai*, Yu Shi, Hong Yan, Xiao-Fei Zhang, Biomarker identification and cancer classification based on microarray data using Laplace naive Bayes model with mean shrinkage, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2012, 9(6):1649~1662.

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