师资队伍

张晓飞

学习经历:

  1. 2008.9 - 2013.6    中山大学,应用数学,博士,导师:戴道清教授

  2. 2004.9 - 2008.6    华中师范大学,信息与计算科学,本科

 

工作经历:

  1. 2013.1 - 2013.7    香港城市大学,研究助理, 合作导师:严洪教授(IEEE Fellow,IAPR Fellow)

  2. 2013.7 - 至今  华中师范大学数学与统计学学院, 讲师

 

获奖情况:

  1. 2012 - 2013年 研究生国家奖学金(金额三万元)


学术兼职:  

  1. 审稿情况:IEEE Transactions on Nanobioscience, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Pacific-Asia Conference on Knowledge Discovery andData Mining (PAKDD)

研究方向生物统计统计学习机器学习网络科学

研究内容:统计学习理论及其在生物信息学和计算机视觉中的应用
   1. 算法理论方面:稀疏正则化、结构化稀疏学习、流形学习、深度学习、半监督学习、谱聚类、概率图模型、随机图模型、图正则化、复杂网络、多类标学习、多任务学习、核方法、变量选择、维数简约、字典学习、压缩感知等理论与算法
   2. 应用方面:生物标志物检测、疾病基因预测、蛋白质功能分析、蛋白质复合体发现、蛋白质三维结构研究、网络医学、个体化医疗、鲁棒人脸识别及图像理解  

 

承担项目:
2. 2015.01 - 2017.12  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, 国家自然科学基金-青年项目, 61402190, 经费24万元
1. 2012.09 - 2013.06   基于图模型的蛋白质相互作用网络的结构及功能研究,中山大学博士研究生创新人才培养资助项目,经费2万元  


参与项目:

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

专利情况:
2.一种基于学生t分布的癌症亚型生物标志物检测系统发明/设计人:吴梦云;戴道清;张晓飞;朱媛,申请号:CN201310190673.3, 公开号:CN103268431A,公开/公告日:20130828
1. 蛋白质复合体挖掘的加权组装聚类方法发明/设计人:欧阳乐;戴道清;张晓飞,申请号:CN201310104854.X, 公开号:CN103235900A,公开/公告日:20130807


期刊论文:  

论文中涉及算法源程序可从以下网址下载:https://github.com/Zhangxf-ccnu

[17] Xiao-Fei Zhang (co-first author), Le Ou-Yang (co-first author), Dao-Qing Dai, Meng-Yun Wu, Yuan Zhu and Hong Yan. Comparative analysis of housekeeping and tissue-specific driver nodes in human protein interaction networks. BMC Bioinformatics, accept, 2017

[16] Le Ou-Yang, Xiao-Fei Zhang (co-first author),, Dao-Qing Dai, Meng-Yun Wu, Yuan Zhu, Zhiyong Liu and Hong Yan. Protein complex detection based on partially shared multi-view clustering.  BMC Bioinformatics, accept, 2017

[15] Meng-Yun Wu, Xiao-Fei Zhang (co-first author),, 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, Feb. 2016, 17:108, doi: 10.1186/s12859-016-0951-7

[14] 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, Feb. 2016, 17:100, doi: 10.1186/s12859-016-0939-3

[13] Xiao-Fei Zhang, Le Ou-Yang, Xiaohua Hu and Dao-Qing Dai, . Identifying binary protein-protein interactions from affinity purification mass spectrometry data,.  BMC Genomics, Oct. 5, 2015, vol. 16:745 doi:10.1186/s12864-015-1944-z
[12] L. Ou-Yang, D. Q. Dai, and
X. F. Zhang, Detecting protein complexes from signed protein-protein interaction networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 12, no. 6, 1333 - 1344, 2015.. (source code)
[11]
X. F. Zhang, L. Ou-Yang, Y. Zhu, M. Y. Wu, and D. Q. Dai, Determining minimum set of driver nodes in protein-protein interaction networks, BMC Bioinformatics, vol. 16:146, 2015.  (source code)
[10] L. Ou-Yang, D. Q. Dai, X. L. Li, M. Wu,
X. F. Zhang and P. Yang, Detecting temporal protein complexes from dynamic protein-protein interaction networks, BMC Bioinformatics, vol. 15:335, October 2014.
[9]
X. F. Zhang, D. Q. Dai, L. Ou-Yang and H. Yan, Detecting overlapping protein complexes based on a generative model with functional and topological properties, BMC Bioinformatics, vol. 15:186, June 2014. (source code)
[8] M. Y. Wu, D. Q. Dai,
X. F. Zhang and Y. Zhu, Cancer subtype discovery and biomarker identification via a new robust network clustering algorithm, PLoS ONE, vol. 8, issue 6, e66256, June 2013.
[7] L. Ou-Yang, D. Q. Dai and
X. F. Zhang,Protein complex detection via weighted ensemble clustering based on Bayesian nonnegative matrix factorization, PLoS ONE, vol. 8, issue 5, e62158, May 2013.
[6] X. X. Li, D. Q. Dai,
X. F. Zhang and C. X. Ren, Structured sparse error coding for face recognition with occlusionIEEE Transactions on Image Processing, vol. 22, no.5, 1889-1990, 2013.
[5] Y. Zhu,
X. F. Zhang, D. Q. Dai and M. Y. 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, vol.10, no.1, 219-225, 2013
[4] M. Y. Wu, D. Q. Dai, Y. Shi, H. Yan and
X. F. 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, vol. 9, no. 6, 1649 -1662, 2012.
[3]
X. F. Zhang, D. Q. Dai, L. Ou-Yang and M. Y. Wu, Exploring overlapping functional units with various structure in protein interaction networks, PLOS ONE, vol. 7, issue 8, e43092, 2012. (source code)
[2]
X. F. Zhang, D. Q. Dai and X. X. 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, vol. 9, no. 3, 857-870, 2012.  (source code)
[1]
X. F. Zhang and D. Q. Dai, A framework for incorporating functional interrelationships into protein function prediction algorithms, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 3, 740-753, 2012.

会议论文
[1] X. X. Li, D. Q. Dai, X. F. Zhang and C. X. Ren, Face recognition with continuous occlusion using partially iteratively reweighted sparse coding, The First Asian Conference on Pattern Recognition (ACPR'11), November 28‐30, 2011, Beijing, China. (EI Index)  

办公地址:华中师范大学数学与统计学学院 科学会堂附楼110室
通讯地址:武汉市华中师范大学数学与统计学学院,430079
         School of Mathematics and Statistics, Central China Normal University
         Wuhan, 430079, P.R. china
Email: zhangxf@mail.ccnu.edu.cn
Google Profile: http://scholar.google.com.hk/citations?user=mGTGvmUAAAAJ&hl=en  

     (最后更新日期:2016-09-01)
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