科研主页

Junhua Zhang received her Ph.D. degree in operational research and cybernetics from the Institute of Systems Science, Chinese Academy of Sciences (CAS), Beijing, China, in 1995. Now she is an associate professor at the Institute of Applied Mathematics, Academy of Mathematics and Systems Science, CAS.


Dr. Zhang is a research fellow at Center of Bioinformatics, Academy of Mathematics and Systems Science, CAS; National Center for Mathematics and Interdisciplinary Sciences, CAS; and Key Laboratory of Random Complex Structures and Data Science, CAS. She is a reviewer of many international journals, including Cancer Research, Scientific Reports, Bioinformatics, PLOS Computational Biology, Information Sciences, Molecular BioSystems, Oncotarget, Physica A, BMC Syst Biol, Mod Phys Lett B, etc.


Dr. Zhang has worked on problems in probability theory, stochastic approximation and its applications, feature extraction in pattern recognition, information measures and their applications. Her current research interests include computational systems biology, data mining and network science.


Research Interests

Cancer Genomics

Understanding the mechanism of carcinogenesis has been a great challenge for human. With the rapid advance in deep sequencing technologies, several large-scale cancer projects have generated an unprecedented amount of cancer genomics data, which has provided tremendous opportunities for the better understanding on cancer initiation, progression and development. Deciphering those data poses great challenges and computational problems for the community of bioinformatics and computational biology. One of such key challenges is to distinguish driver mutations, genes as well as pathways from passenger ones. We mainly aim to develop computational methods (models and algorithms) to identify cancer driver genes or pathways to enhance understanding for carcinogenesis.

Network Science

Many real-world systems can be represented by networks composed of vertices and edges, such as biological networks, social networks, etc. Usually the functions of the systems are closely related to the network structures (in biology, network medicine). We aim to develop models and algorithms to uncover the topological organization of complex networks to better understand the mechanisms underlying complex diseases, biological systems and other complex systems. Among others, community structure detection of complex networks attracts a great deal of attention in various disciplines, which means the division of networks into groups (also called clusters) having dense intraconnections, and sparse interconnections.

Information Measures

Information measures, such as Shannon entropy, mutual information, Kullback–Leibler information, etc., are quantities measuring the information about random outcomes which are described by probability distributions. We mainly focused on proposing some new information measures, and then analyzing their properties and applying them to other disciplines.

Stochastic Approximation

Stochastic approximation (SA)methods are a family of iterative stochastic optimization algorithms that attempt to find zeroes or extrema of functions which cannot be computed directly, but only estimated via noisy observations. We focused on the convergence analysis of some SA algorithms, and on the application research of SA to other disciplines such as pattern recognition and feature extractions.

Selected Journal Papers (* correspondence author)

  1. Junhua Zhang* and Shihua Zhang*, Discovery of cancer common and specific driver gene sets. Nucleic Acids Res. (2017), 45(10): e86

  2. Junhua Zhang and Shihua Zhang, The discovery of mutated driver pathways in cancer: models and algorithms. IEEE/ACM Trans. Comput. Biol. Bioinform. (2016), doi:10.1109/TCBB.2016.2640963

  3. Junhua Zhang*, Ling-Yun Wu, Xiang-Sun Zhang and Shihua Zhang*, Discovery of co-occurring driver pathways in cancer. BMC Bioinformatics (2014), 15: 271 (Highly Accessed)

  4. Junhua Zhang*, Shihua Zhang*, Yong Wang and Xiang-Sun Zhang, Identification of mutated core cancer modules by integrating somatic mutation, copy number variation, and gene expression data. BMC Systems Biology (2013), 7: S4

  5. Hui-Jia Li, Junhua Zhang, Zhi-Ping Liu, Luonan Chen and Xiang-Sun Zhang, Identifying overlapping communities in social networks using multi-scale local information expansion. Eur. Phys. J. B (2012) , 85: 190

  6. Hui-Jia Li, Yong Wang, Ling-Yun Wu, Junhua Zhang and Xiang-Sun Zhang, Potts model based on a Markov process computation solves the community structure problem effectively. Physical Review E (2012), 86: 016109

  7. Junhua Zhang*, Yuqing Qiu and Xiang-Sun Zhang, Detecting community structure: from parsimony to weighted parsimony. Journal of Systems Science and Complexity (2010), 23: 1024-1036

  8. Junhua Zhang*, Shihua Zhang and Xiang-Sun Zhang, Detecting community structure in complex networks based on a measure of information discrepancy. Physica A (2008), 387: 1675-1682

  9. Min Zhang, Weiwu Fang, Junhua Zhang and Zhongxian Chi, MSAID: Multiple Sequence Alignment Based on a Measure of Information Discrepancy. Computational Biology and Chemistry (2005), 29: 175-181

  10. Junhua Zhang and Weiwu Fang, A new approach of information discrepancy to analysis of questionnaire data. Communications in Statistics – Theory and Methods (2003), 32: 435-457

  11. Shihua Chen, Junhua Zhang and Todd Young, Existence of positive periodic solution for nonautonomous predator-prey system with diffusion and time delay. Journal of Computational and Applied Mathematics (2003), 159: 375-386

  12. Junhua Zhang*, On Lyapunov functions in stochastic approximation. Mathematica Applicata (2001), 14: 56-60

  13. Junhua Zhang and Weiwu Fang, A new statistic for variable selection in questionnaire analysis, J. Syst. Sci. Syst. Eng. (2001), 10: 315-322

  14. Junhua Zhang*, Convergence of algorithms for finding eigenvectors. Acta Mathematicae Applicatae Sinica (English Series) (2000), 16: 355-361

  15. Junhua Zhang and Hanfu Chen, Convergence of algorithms used for principal component analysis. Science in China (Series E) (English Series) (1997), 40: 597-604

Selected Conference Papers (* correspondence author)

  1. Junhua Zhang*, Shihua Zhang*, Yong Wang, Junfei Zhao and Xiang-Sun Zhang, Identifying mutated core modules in glioblastoma by integrative network analysis. Proceedings of IEEE 6th International Conference on Systems Biology (2012), 304-309

  2. Junhua Zhang*, Zhi-Ping Liu, Xiang-Sun Zhang and Luonan Chen, A dynamical method to extract communities induced by low or middle-degree nodes. Proceedings of IEEE 5th International Conference on Systems Biology (2011), 340-344

  3. Shoujun Xu, JiguangWang, Junhua Zhang and Xiang-Xun Zhang, Multiple resolution community structure analysis. Lecture Notes in Operations Research 14: Operations Research and Its Applications (2011), 334-349

  4. Junhua Zhang* and Xiang-Sun Zhang, On resolution limit of the modularity in community detection. Lecture Notes in Operations Research 12: Operations Research and Its Applications (2010), 492-499

  5. Junhua Zhang, Wentao Huang, Zhiyuan Zhao, Biao Li, Yuelan Wang, Dongfeng Gu, Guoying Li, and Rensheng Chen, Study on multilocus interactions for hypertension by an information theoretic method. Lecture Notes in Operations Research 11: Optimization and Systems Biology (2009), 456-467

  6. Junhua Zhang* and Xiang-Sun Zhang, A weighted parsimony model for community detection in complex networks. Lecture Notes in Operations Research 11: Optimization and Systems Biology (2009), 419-429

  7. Junhua Zhang* and Shihua Chen, A random iterative algorithm for community detection. Lecture Notes in Operations Research 11: Optimization and Systems Biology (2009), 448-455

  8. Junhua Zhang*, Shihua Zhang and Xiang-Sun Zhang, Comparative study on a class of evaluation indices for community detection. Lecture Notes in Operations Research 9: Optimization and Systems Biology (2008), 294-303

  9. Junhua Zhang*, Weihua Yue, and Xiang-Sun Zhang, Multilocus analysis of casecontrol data to schizophrenia based on measures of information discrepancy. Lecture Notes in Operations Research 8: Operations Research and Its Applications (2008), 432- 439

  10. Junhua Zhang and Weiwu Fang, Asymptotic distributions of a measure of information discrepancy among multiple discrete distributions. Proceedings of ORSC, Hong Kong: Global-Link Publishing Company (2004), 1278-1787

  11. Junhua Zhang and Weiwu Fang, Some methods to variable selection in questionnaire analysis. Proceedings of ORSC, Hong Kong: Global-Link Publishing Company (2000), 889-896

People

Kangning Dong
Graduate student
Kuo Gai
Graduate student
Qunlun Shen
Graduate student
Rui Wang
Graduate student

Contact

Address: Academy of Mathematics and Systems Science, CAS, No.55, Zhongguancun East Road, Beijing 100190, China

Tel: 010 - 82541364

Email: zjh@amt.ac.cn