Jing Zhang

Associate Professor (08/2021 ~ present)

Assistant Professor (08/2014 ~ 2021)

Department of Mathematics and Statistics, Georgia State University

Assistant Professor (07/2010 ~ 06/2014)

Department of Statistics, Yale University

Education

• • Postdoctoral fellow, 06/2009 ~ 05/2010, Department of Statistics, Harvard University

  • Ph.D, 06/2009, Department of Statistics, Harvard University

  • MA, 03/2007, Department of Statistics, Harvard University

  • MA, 07/2005, Bioinformatics, Tsinghua University

  • BS, 07/2002, Automation, Tsinghua University

Teaching

• • Fall 2010, Data Analysis

  • Spring 2011, Statistical methods in Genetics and Bioinformatics.

  • Fall 2011, Probability and Statistics

  • Spring 2012, Stochastic Process

  • Spring 2012, Statistical methods in Genetics and Bioinformatics

  • Fall 2012~Fall 2013, on leave

  • Fall 2013, Topics in Bayesian Inference and Data Analysis

  • Spring 2014, Statistical methods in Genetics and Bioinformatics

  • Fall 2014, Mathematical statistics

  • Spring 2015, Computational methods in Statistics

  • Fall 2015, Applied Bayesian Statistics

  • Spring 2016, Mathematical Statistics

  • Spring 2016, Computational methods in Statistics

  • Fall 2016, Mathematical Statistics

  • Fall 2016, Linear Statistical Analysis

  • Spring 2017, Mathematical Statistics

  • Spring 2017, Computational methods in Statistics

  • Fall 2017, Linear Statistical Analysis

  • Spring 2018, Bayesian Data Analysis

  • Fall 2018, Mathematical Statistics

  • Fall 2018, Linear Statistical Analysis

  • Spring 2019, Computational methods in Statistics

  • Spring 2019, Mathematical Statistics

  • Fall 2019, Mathematical Statistics II

  • Fall 2019, Linear Statistical Analysis

  • Spring 2020, Computational methods in Statistics

  • Spring 2020, Mathematical Statistics I

  • Fall 2020, Mathematical Statistics II

  • Fall 2020, Linear Statistical Analysis

  • Spring 2021, Computational methods in Statistics

  • Spring 2021, Mathematical Statistics I

  • Fall 2021, Applied Probability and Statistics for Computer Science 

  • Spring 2022 Applied Bayesian Statistics

  • Fall 2022 Mathematical Statistics I

  • Fall 2022 Linear Statistical Analysis

  • Spring 2023 Applied Bayesian Statistics

  • Spring 2023 Mathematical Statistics I

  • Fall 2023 Mathematical Statistics II

  • Fall 2023 Linear Statistical Analysis
    
    

Official students' evaluation from GSU

2023 fall Math 6752, totally 4 graduate students are enrolled. The student evaluation is 4-5 out of 5.

2023 fall Math 4752, totally 18 undergrad students are enrolled. The student evaluation is 3.5-4.4 out of 5.

2023 fall Stat 8561, totally 54 graduate students are enrolled. The student evaluation is 4.5-4.9 out of 5

2023 spring Math 6751, totally 3 graduate students are enrolled. The student evaluation is 4-5 out of 5.

2023 spring Math 4751, totally 31 undergrad students are enrolled. The student evaluation is 3.7-4.9 out of 5.

2023 spring Stat 8310, totally 60 graduate students are enrolled. The student evaluation is 4.6-4.8 out of 5

2022 fall Stat 8561, totally 38 graduate students are enrolled. The student evaluation is 4.2-4.9 out of 5

2022 fall Math 6751, totally 5 graduate students are enrolled. The student evaluation is 4.5 out of 5.

2022 fall Math 4751, totally 18 undergrad students are enrolled. The student evaluation is 3.4-5 out of 5.

2022 spring Stat 8310, totally 30 graduate students are enrolled. The student evaluation is 4.2-4.8 out of 5

2021 fall Math 3020 MW, totally 76 undergrad students are enrolled. The student evaluation is 3.4-4.3 out of 5.

2021 fall Math 3020 TR, totally 22 undergrad students are enrolled. The student evaluation is 4.1-4.9 out of 5.

2021 spring Stat 8670, totally 22 graduate students are enrolled. The student evaluation is 3.5-4.1 out of 5

2021 spring Math 6751, totally 11 graduate students are enrolled. The student evaluation is 4.3-5 out of 5.

2021 spring Math 4751, totally 40 undergrad students are enrolled. The student evaluation is 4.1-4.8 out of 5.

2020 fall Stat 8561, totally 39 graduate students are enrolled. The student evaluation is 4-4.7 out of 5

2020 fall Math 6752, totally 14 graduate students are enrolled. The student evaluation is 4-4.9 out of 5.

2020 fall Math 4752, totally 31 undergrad students are enrolled. The student evaluation is 3.4-4.3 out of 5.

2020 spring Stat 8670, totally 35 graduate students are enrolled. The student evaluation is not available due to COVID19

2020 spring Math 6751, totally 11 graduate students are enrolled. The student evaluation is not available due to COVID19.

2020 spring Math 4751, totally 60 undergrad students are enrolled. The student evaluation is not available due to COVID19.

2019 fall Stat 8561, totally 23 graduate students are enrolled. The student evaluation is 3.9-4.3 out of 5

2019 fall Math 6752, totally 4 graduate students are enrolled. The student evaluation is 4.5-5 out of 5.

2019 fall Math 4752, totally 13 undergrad students are enrolled. The student evaluation is 3.5-5 out of 5.

2019 spring Stat 8670, totally 34 graduate students are enrolled. The student evaluation is 3.8 out of 5

2019 spring Math 6751, totally 6 graduate students are enrolled. The student evaluation is 4.7 out of 5.

2019 spring Math 4751, totally 51 undergrad students are enrolled. The student evaluation is 2.6 out of 5.

2018 fall Stat 8561, totally 38 graduate students are enrolled, the student evaluation is 4.5 out of 5

2018 fall Math 6751, totally 11 grad students are enrolled. The student evaluation is 4.2 out of 5.

2018 fall Math 4751, totally 71 undergrad students are enrolled. The student evaluation is 3.9 out of 5.

2018 spring Stat  8310 BAYESIAN DATA ANALYSIS, totally 38 graduate students are enrolled, the student evaluation is 4.6 out of 5

2017 fall Stat 8561, totally 31 graduate students are enrolled, the student evaluation is 4.6 out of 5

2017 spring Math 4751, totally 72 undergrad students are enrolled. The student evaluation is 4.1 out of 5.

2017 spring Math 6751, totally 11 grad students are enrolled. The student evaluation is 4.3 out of 5.

2017 spring Stat 8670, totally 18 grad students are enrolled. The student evaluation is 4.4 out of 5.

2016 spring Math 4751, totally 32 undergrad students are enrolled. The student evaluation is 3.8 out of 5.

2016 spring Math 4751 Honor, 2 undergrad students are enrolled. The student evaluation is 5 out of 5.

2016 spring Math 6751, 8 graduate students are enrolled. The student evaluation is 4.8 out of 5.

2016 spring Stat 8670, totally 41 graduate students are enrolled . The student evaluation is  4.5 out of 5.

2016 fall Math 4751, totally 70 undergrad students are enrolled. The student evaluation is 4.1 out of 5.

2016 fall Math 6751, 8 graduate students are enrolled. The student evaluation is 4.2 out of 5.

2016 fall Stat 8561, totally 27 graduate students are enrolled, the student evaluation is 4.7 out of 5

2015 spring Stat 8670, totally 39 graduate students are enrolled . The student evaluation is  4.1 out of 5.

2015 fall Stat 8310, totally 45 graduate students are enrolled . The student evaluation is  4.0 out of 5.

2014 fall Math 4751 totally 46 undergrad students are enrolled. The student evaluation is  4.0 out of 5,

2014 fall Math 6751 totally 8 graduate students are enrolled. The student evaluation is 4.5 out of 5.

Research Interests

• • Bayesian inference on complicated interactions, Big data analysis

  • NeuroImage analysis, Brain mapping

  • Statistical genetics, Epigenetics

  • Genome-wise Association for human complex diseases

  • Computational Virology, HIV drug resistance, viral and human genetic markers underlying the progression of persistent viral infection sustained by HIV, HBV, and HCV

  • Computational biology and Bioinformatics

  • Bayesian network, Graph Models

  • Biomedical image analysis, computational neuroscience, and biomedical informatics

Professional Activities

• • Leading guest Editor (with Dr Tianming Liu and Dr Gopikrishna Deshpande): Special Issue on IEEE/ACM Transactions on Computational Biology and Bioinformatics

  • Editorial member: Frontiers in Computational Neuroscience

  • Invited reviewer for NSF/NIH grant review panel

  • Invited reviewer for Wellcome Trust and Royal Society: Sir Henry Dale Fellowship

  • Review papers for

  • Journal of the American Statistical Association (JASA), Statistica Sinica, the plant Cell, Annals of Applied Statistics, Biostatistics, Bioinformatics, BMC Bioinformatics, NeuroImage, PLoS One, PLoS Computational Biology, Statistical Applications in Genetics and Molecular Biology, Cell Research, BMC Genetics, BMC Research Note, Journal of Probability and Statistics, Asia Pacific Bioinformatics Conference, Computational Statistics and Data Analysis, IEEE Transactions on Computational Biology and Bioinformatics, Journal of Agricultural, Biological, and Environmental Statistics, IEEE Transactions on Autonomous Mental Development，Brain Imaging and Behavior，Brain informatics，Frontiers in Computational Neuroscience，Genetics Research， Journal of bioinformatics and proteomics review, Journal of Selected Topics in Signal Processing,   etc.

Publications

• 1. Spatial Analysis of Retinal Pigment Epithelial Morphology in Mice. Huang H, Donaldson K.,Zhang J., Priyadarshani P.,Grossniklaus H.,Nickerson J. , Boatright J., Jiang Y., (2019) submitted to Investigative Ophthalmology & Visual Science (IOVS).

  2. Bayesian Analysis of Complex Mutations in HBV, HCV,and HIV Studies. Bing Liu, Shishi Feng, Xuan Guo and Jing Zhang (corresponding author) (2019) accepted. Big Data Mining and Analytics. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8681051

  3. Large-scale circuitry interactions upon earthquake experiences revealed by Recurrent Neural Networks. (2018) Han Wang, Kun Xie, Zhichao Lian, Yan Cui, Yaowu Chen, Jing Zhang, Leo Xie, Joe Tsien, Tianming Liu. accepted. IEEE Transactions on Neural Systems & Rehabilitation Engineering

  4. Bayesian Bi-Cluster Change-Point Model for Exploring Functional Brain Dynamics. Bing Liu, Xuan Guo, Jing Zhang(corresponding author) (2018) The 19th International Conference on Bioinformatics & Computational Biology

  5. Editorial: Probablistic methods in Computational Neuroscience. (2018) Jing Zhang, Tianming Liu,  Gopikrishna Deshpande ,   IEEE/ACM Transactions on Computational Biology and Bioinformatics. vol 15, issue 2.

  6. An Optimized method for Bayesian Connectivity Change Point Model. Xiuchun Xiao, Bing Liu, Jing Zhang(joint corresponding author), Xueli Xiao, Yi Pan. Journal of Computational Biology, accepted. 2017

  7. Detecting Change Points in fMRI Data via Bayesian Inference and Genetic Algorithm Model.（2017）Xiuchun Xiao, Bing Liu, Jing Zhang, Xueli Xiao and Yi Pan. ISBRA 2017 accepted.published on the book Bioinformatics research and Applications.

  8. Bayesian Inference for Functional Dynamics Exploring in fMRI Data. (2016) Xuan Guo, Bing Liu, Le Chen, Guantao Chen, Yi Pan and Jing Zhang (corresponding author). Computational and Mathematical Methods in Medicine. vol. 2016, Article ID 3279050, 9 pages, 2016. doi:10.1155/2016/3279050.

  9. A Bayesian Model for Detection of High-order Interactions among Genetic Variants in Genome-wide Association Studies. (2016) Juexin Wang; Trupti Joshi; Babu Valliyodan; Haiying Shi; Yanchun Liang; Henry Nguyen; Jing Zhang (joint corresponding authors); Dong Xu. BMC Genomics Accepted. http://digbio.missouri.edu/BHIT/

  10. Searching Genome-wide Multi-locus Associations for Multiple Diseases Based on Bayesian Inference. (2016) Xuan Guo, Jing Zhang*, Zhipeng Cai, Ding-Zhu Du, and Yi Pan* (* joint corresponding authors). IEEE/ACM Transactions on Computational Biology and Bioinformatics.

  11. Searching Genome-wide Disease Associations in Case-control Studies. (2015) Jing Zhang, Xuan Guo, Yi Pan. Journal of Bioinformatics and Proteomics Review. 1(1): 1-2

  12. Dynamic Bayesian Brain Network Partition and Connectivity Change Point Detection. (2015) Zhichao Lian, Xiang Li, Yi Pan, Xuan Guo, Le Chen, Guantao Chen, Zhihui Wei, Tianming Liu and Jing Zhang. ICCABS 2015

  13. Investigating Genotype 1a HCV Drug Resistance in NS5A region via Bayesian inference. Yao Fu, Gang Chen, Lizhi Fu, Jing Zhang (corresponding author). (2015) Tsinghua Science and Technology

  14. Analyzing the Effects of Pretreatment Diversity on HCV Drug Treatment Responsiveness using Bayesian Partition method. (2015) Yao Fu, Gang Chen, Xuan Guo, Yi Pan, Jing Zhang (corresponding author). Journal of Bioinformatics & Proteomics Review. Accepted.

  15. DAM: A Bayesian Method for Genome-wide Associations Detecting on Multiple Diseases. (2015) Xuan Guo, Jing Zhang*, Zhipeng Cai, Ding-Zhu Du, and Yi Pan* (* joint corresponding authors). ISBRA 2015. Accepted. also in The book Bioinformatics Research and Applications. Springer

  16. Specific mutations in the C-terminus domain of HBV surface antigen significantly correlate with low level of serum HBV-DNA in patients with chronic HBV infection (2015) Carmen Mirabelli; Matteo Surdo; Formijn Van Hemert; Zhichao Lian; et al. Jing Maria Zhang; Massimo Andreoni; Mario Angelico; Jens Verheyen; Francesca Ceccherini-Silberstein; Carlo Federico Perno; Valentina Svicher. Journal of Infection.doi:10.1016/j.jinf.2014.10.015

  17. Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models. (2015) Jinli Ou, Li Xie, Changfeng Jin, Xiang Li, Dajiang Zhu, Rongxin Jiang, Yaowu Chen, Wei Hao, Jing Zhang (joint corresponding author), Lingjiang Li, Tianming Liu. Brain Topography (BTOP). Accepted

  18. Sparse Representation of Whole-brain FMRI Signals for Identification of Functional Networks. Jinglei Lv, Xi Jiang, Xiang Li, Dajiang Zhu, Hanbo Chen, Tuo Zhang, Shu Zhang, Xintao Hu, Junwei Han, Heng Huang, Jing Zhang, Lei Guo, Tianming Liu. Medical Image Analysis. 20:112-134 (2015)

  19. Atomic Connectomics Signatures for Characterization and Differentiation of Mild Cognitive Impairment. (2015) Jinli Ou, Li Xie, Xiang Li, Dajiang Zhu, Douglas P. Terry, A. Nicholas Puente, Rongxin Jiang, Yaowu Chen, Lihong Wang, Dinggang Shen, Jing Zhang, L. Stephen Miller, Tianming Liu. Brain Imaging and Behavior. Accepted.

  20. Atomic Dynamic Functional Interaction Patterns for Characterization of ADHD (2014) Jinli Ou, Zhichao Lian, Li Xie, Xiang Li, Peng Wang, Yun Hao, Dajiang Zhu, Rongxin Jiang, Yufeng Wang, Yaowu Chen, Jing Zhang (joint corresponding author), Tianming Liu. Human Brain Mapping, 35: 5262.

  21. Inferring Functional Interaction and Transition Patterns via Dynamic Bayesian Variable Partition Model. (2014) Jing Zhang (first and corresponding author), Xiang Li, Cong Li, Xiu Huang, Guocheng Zhong, Dajiang Zhu, Kaiming Li, Xi Jiang, Changfeng Jin, Xintao Hu, Junwei Han, Lei Guo, Xiaoping Hu, Lingjiang Li, Tianming Liu. Accepted. Human Brain Mapping. Software can be found here.

  22. Dynamic Functional Connectomics Signatures for Characterization and Differentiation of PTSD Patients. Xiang Li, Dajiang Zhu, Xi Jiang, Changfeng Jin, Xin Zhang, Lei Guo, Jing Zhang, Xiaoping Hu, Jingjiang Li, Tianming Liu. (2014) Human Brain Mapping. Accepted.

  23. Detecting cell assembly interaction patterns via Bayesian based change-point DETECTION and GRAPH Inference model. (2014) Zhichao Lian, Xiang Li, Hongmiao Zhang, Hui Kuang, Kun Xie, Jianchuan Xing, Dajiang Zhu, Joe Z. Tsien, Tianming Liu, Jing Zhang (corresponding author). ISBI 2014 - IEEE International Symposium on Biomedical Imaging.

  24. Generalized FMRI Activation Detection via Bayesian Magnitude Change Point Model. (2014) Zhichao Lian, Jinglei Lv, Jianchuan Xing, Xiang Li, Xi Jiang, Dajiang Zhu, Jiansong Xu, Marc N. Potenza, Tianming Liu, Jing Zhang (corresponding author). ISBI 2014 - IEEE International Symposium on Biomedical Imaging.

  25. Exploring functional brain dynamics via a Bayesian connectivity change point model. (2014) Zhichao Lian, Xiang Li, Jianchuan Xing, Jinglei Lv, Xi Jiang, Dajiang Zhu, Jiansong Xu, Marc N. Potenza, Tianming Liu, Jing Zhang (corresponding author). ISBI 2014 - IEEE International Symposium on Biomedical Imaging.

  26. Dynamic Network Partition Via Bayesian Connectivity Bi-Partition Change Point Model (2014) Zhichao Lian, Xiang Li, Thomas Young, Yun Hao, Jianchuan Xing, Jinglei Lv, Xi Jiang, Dajiang Zhu, Tianming Liu, Jing Zhang (corresponding author). ISBI 2014 - IEEE International Symposium on Biomedical Imaging.

  27. P691 KEY PATTERNS OF HBsAg MUTATIONS CORRELATE WITH MECHANISMS UNDERLYING LEVELS OF SERUM HBVDNA. M. Surdo, M.F. Cortese, C. Mirabelli, R. Salpini, J. Zhang, F. Van Hemert, V. Cento, M. Pollicita, G. Gubertini, G.M. De Sanctis, P. Trimoulet, H. Fleury, F. Mazzotta, R. Longo, G. Cappiello, A. Span, C. Sarrecchia, M. Andreoni, M. Angelico, J. Verheyen, C.F. Perno, V. Svicher. (2014) Journal of Hepatology 04/2014; 60(1):S299. DOI:10.1016/S0168-8278(14)60853-9

  28. Modeling Brain Functional Dynamics via Hidden Markov Models. (2013) Jinli Ou, Li Xie, Peng Wang, Xiang LI, Dajiang Zhu, Rongxin Jiang, Yufeng Wang, Yaowu Chen, Jing Zhang* (joint corresponding author), Tianming Liu. The 6th International IEEE EMBS Conference on Neural Engineering. NER 2013.

  29. Detecting hepatitis B viral amino acid sequence mutations in occult hepatitis B infections via Bayesian partition model. (2013) ZHICHAO LIAN, QI NING TIAN, YANG LIU, VALERIA CENTO, ROMINA SALPINI, CARLO FEDERICO PERNO, VALENTINA SVICHER, GANG CHEN, CONG LI, JING ZHANG (corresponding author). Journal of Proteomics & Bioinformatics. Accepted

  30. Identifying Functional Networks via Sparse Coding of Whole Brain FMRI signals. (2013) Jinglei Lv*, Xi Jiang, Xiang LI, Dajiang Zhu, Hanbo Chen, Tuo Zhang, Shu Zhang, Xintao Hu, Junwei Han, Heng Huang, Jing Zhang, Lei Guo, Tianming Liu. The 6th International IEEE EMBS Conference on Neural Engineering. NER 2013.

  31. Group-wise Change Point Detection in Task FMRI Data by Bayesian Methods. (2013) Jianchuan Xing, Jinglei Lv, Zhichao Lian, Xiang LI, Dajiang Zhu, Tianming Liu, Jing Zhang (corresponding author). The 6th International IEEE EMBS Conference on Neural Engineering. NER 2013

  32. Detecting and understanding genetic and structural features in HIV-1 B subtype V3 underlying HIV-1 co-receptor usage. (2013) Mengjie Chen, Valentina Svicher, Anna Artese, Giosu Costa, Claudia Alteri, Francesco Ortuso, Lucia Parrotta, Yang Liu, Chang Liu, Carlo Federico Perno, Stefano Alcaro, Jing Zhang (corresponding author). Bioinformatics 2013 Feb 15;29(4):451-60. doi: 10.1093/bioinformatics/btt002..

  33. Neighborhood Preserving Ordinal Regression. Yang Liu, Yan Liu, Keith C.C. Chan, Jing Zhang. (2012) ACM ICIMCS, the International Conference on Internet Multimedia Computing and Service. Indexed by EI.

  34. Bayesian Exploration of Multilocus Interactions on the Genome-Wide Scale. Kozyryev I and Zhang J (corresponding author). Accepted by American Journal of Bioinformatics. Vol 1, Page Numbers: 70-78 (2012) DOI: 10.3844/ajbsp.2012.70.78

  35. High-Order Interactions in Rheumatoid Arthritis Detected by Bayesian Method using Genome-Wide Association Studies Data. (2012) Jing Zhang (first and corresponding author), Zheyang Wu, Chao Gao and Michael Q. Zhang. American Medical Journal, Volume 3, Issue 1, Pages 56-66, DOI: 10.3844/amjsp.2012.56.66 Supplementary Material can be downloaded from http://www.stat.yale.edu/~jz349/RA_paper/SupplementaryMaterials.zip

  36. Inferring Consistent Functional Interaction Patterns from Natural Stimulus FMRI Data. (2012) Jiehuan Sun, Xintao Hu, Xiu Huang, Yang Liu, Kaiming Li, Xiang Li, Junwei Han, Lei Guo, Tianming Liu, Jing Zhang (corresponding author). NeuroImage Volume 61, issue 4, page 987-999.

  37. Systematic Investigation on Interactions for HIV Drug Resistance and Cross-Resistance among Protease Inhibitors. (2012) Jing Zhang (first and corresponding author), Tingjun Hou, Yang Liu, Gang Chen, Xiao Yang, Jun S Liu and Wei Wang. Journal of Proteome Science & Computational Biology 2012 1: 2. DOI : http://dx.doi.org/10.7243/2050-2273-1-2

  38. Bayesian Determination of Disease Associated Differences in Haplotype Blocks. Kozyryev I and Zhang J (corresponding author).American Journal of Bioinformatics, Volume 1, Issue 1, Pages 20-29 DOI: 10.3844/ajbsp.2012.20.29 (2012)

  39. Novel HBsag markers tightly correlate with occult HBV infection and strongly affect HBsag detection. Valentina Svicher; Valeria Cento; Martina Bernassola; Maria Neumann-Fraune; Formijn Van Hemert; Mengjie Chen; Romina Salpini; Chang Liu; Roberta Longo; Michela Visca; Sara Romano; Valeria Micheli; Ada Bertoli; Caterina Gori; Francesca Ceccherini-Silberstein; Cesare Sarrecchia; Massimo Andreoni; Mario Angelico; Antonella Ursitti; Alberto Span; Jing Maria Zhang; Jens Verheyen; Giuseppina Cappiello; C.F. Perno. Antiviral Research 93(1):86-93. (2012)

  40. A Bayesian Method for Disentangling Dependent Structure of Epistatic Interaction. Zhang, J. (first and corresponding author), Zhang, Q., Lewis, D., Zhang, M. American Journal of Biostatistics. Volume 2, Issue 1 Pages 1-10. DOI: 10.3844/amjbsp.2011.1.10

  41. Block-based Bayesian Epistasis Association Mapping With Application to WTCCC Type 1 Diabetes.(2011) Zhang, Y., Zhang, J., Liu, S.J Annals of Applied Statistics Vol. 5, No. 3, 2052-2077. Software BEAM2 can be downloaded from Yu Zhang's webpage: http://www.stat.psu.edu/~yuzhang/

  42. Identification and structural characterization of novel genetic elements in the HIV-1 V3 loop regulating coreceptor usage. Valentina Svicher, Claudia Alteri, Anna Artese, Fabio Mercurio, Jing Zhang, Giosu Costa, R D'Arrigo, Stefano Alcaro, Giorgio Pal, Massimo Clementi, Maurizio Zazzi, Massimo Andreoni, Andrea Antinori, Adriano Lazzarin, Francesca Ceccherini-Silberstein, Carlo Federico Perno on behalf of the OSCAR study group. Antiviral Therapy 16(7):1035-45 (2011)

  43. Key-genetic Elements in HIV-1 gp120 V1, V2, and C4 Domains Tightly and Differentially Modulate gp120 Interaction with the CCR5 and CXCR4 N-terminus and HIV-1 Antigenic Potential. V Svicher, M Chen, C Alteri, G Costa, S Dimonte, Chang Liu, L Parrotta, C Dimaio, S Carta, M Surdo, P Saccomandi, S Alcaro, F Ceccherini-Silberstein, A Artese, JM Zhang (joint corresponding author), CF Perno The 2nd International HIV & Hepatitis Virus Drug Resistance Workshop. (2011) ANTIVIRAL THERAPY Volume: 16 Issue: 4 Pages: A14-A14

  44. Specific HBsAg genetic-determinants are associated with occult HBV-infection in vivo and HBsAg-detection. V Svicher, V Cento, M Bernassola, M Neumann-Fraune, M Chen, R Salpini, Chang Liu, R Longo, M Visca, S Romano, V Micheli, A Bertoli, G Gubertini, N Marino, F Mazzotta, C Sarrecchia, M Andreoni, M Angelico, A Ursitti, A Span, F Ceccherini, JM Zhang, J Verhejen, G Cappiello, CF Perno. The 2nd International HIV & Hepatitis Virus Drug Resistance Workshop. (2011) ANTIVIRAL THERAPY, Volume: 16 Issue: 4 Pages: A85-A85

  45. Detecting and understanding combinatorial mutation patterns responsible for HIV drug resistance. Zhang, J., Hou, T., Wei, W., Liu, S.J. (2010) Proceedings of the National Academy of Sciences of the United States of America (PNAS) 107, 1321

      1. Highlight of this paper from PNAS Media Selections:

      2. http://www.pnas.org/site/misc/selections_1_11_10.shtml

      3. http://www.pnas.org/content/107/4/1255.full

      4. Science Daily news on this paper: http://www.sciencedaily.com/releases/2010/01/100111154918.htm

      5. Harvard Crimson's article on this paper:

      6. http://www.thecrimson.com/article/2010/1/14/hiv-drug-resistance-mutations/

      7. UCSD news release on this paper:

      8. http://physicalsciences.ucsd.edu/news/releases/release_detail.php?release_id=281

  46. htSNPer 1.0: software for haplotype block partition and htSNPs selection, Ding K., Zhang J. (joint first author), Zhou K., Shen Y., Zhang X. (2005) BMC Bioinformatics 6, 38. Software is available at here or http://www.chgb.org.cn/htSNPer/htSNPer.html

  47. Evidence and Characteristics of putative human alpha recombination hotspots. Zhang, J., Li, F., Li, J., Zhang, M. Q., Zhang, X. (2004) Hum. Mol. Genet. 13, 2823

  48. The effect of haplotype definitions on inference of haplotype block structure and htSNPs selection, Ding K., Zhou K., Zhang J., Knight J., Zhang X., Shen Y. (2005) Molecular Biology and Evolution, 22, 148-159

  49. Ivan Kozyryev and Jing Zhang (corresponding author). (2014) Chapter 21 The Drug Design for Resistant HIV. Advs Exp. Medicine, Biology Vol. 827, Dongqing Wei et al. (Eds): Advance in Structural Bioinformatics.

  50. Ivan Kozyryev and Jing Zhang (corresponding author). (2017) Clinical Assessment of Disease Risk Factors using SNP Data and Bayesian Methods. In Health Informatics Data Analysis: Methods and Examples. Dong Xu et al. (Eds)

Awards and Grants

• • 2015~2016 Brains and Behavior Seed Grant Georgia State University. Support one Ph.D student

  • 2012 Seessel Award to Junior Faculty, Yale University. Support one postdoc fellow

  • 2011 Seessel Award to Junior Faculty, Yale University. Support one postdoc fellow

  • 2010 Seessel Award to Junior Faculty, Yale University. Support one postdoc fellow

  • 2008 Spring Excellence in Teaching Award Harvard University

  • 2003~2004 Top One Graduate Student Award-Intel Scholarship

  • 2002~2003 Tsinghua University Excellent Graduate student Award

  • 2002 Beijing Excellent Graduate Award

  • 2002 Tsinghua University Outstanding Graduate with Honors

  • 2000~2001 Tsinghua University Excellent Student Award Scholarship-China Weal

  • 1999~2000 Tsinghua University Excellent Student Award Scholarship-Schneider Electric

  • 1998~1999 Tsinghua University Excellent Student Award Scholarship-Schneider Electric

Students and Postdocs mentored

Undergraduate:

• 1. Ivan Kozyryev, Major: Applied Math. 2011, Thesis: Determining Disease associated differences in Linkage Disequilibrium Boundaries using a Bayesian model and MCMC. With distinction.

  2. Diana Shen, Major: Statistics. 2011, Thesis: Statistical Analysis of HIV drug resistance data.

  3. Varoon Kumar Bashyakarla, Major: Statistics, 2012, Thesis: A Genome-wide Association Study of Single Nucleotide Polymorphisms Associated with Hypertension.

  4. Kevin Zhang, Major: Statistics, 2012, Thesis: Bayesian Epistasis Association Mapping Analysis of Type 2 Diabetes.

  5. Gang Chen, Major: Economics, 2012, research Project: HCV Drug Resistance Analysis.

  6. Cameron Musco, Major: Computer Science. Research Project: Bayesian method for detecting rare mutations.

Graduate students:

Tingting Jiang, Wenjing Ge, Steven Wei Ho, Haben Michael, Chao Gao, Chang Liu, Zhixiang Lin, Yao Fu, Seung Hun Lee, Guocheng Zhong, Joseph Kim

On the Ph.D qualifying committee: Mengjie Chen, Lucus Lochovsky

On the Ph.D thesis committee: Rao Fu, Yang Liu

Rotation: Gadareth Higgs, Tingting Jiang

Postdoctoral Associates: Yang Liu, Zhichao Lian.

Visiting professor: Prof. Jianchuang Xing

Invited Talks

• • March 17, 2017 Invited talk to Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University

  • Feb 10, 2016 Invited talk to Department of Biostatistics, UNC

  • Aug. 5-6, 2013 Integrative Biology-2013, Las Vegas, USA

  • Aug. 1, 2013 EITA-YIC 2013, the 3rd EITA Young Investigator Conference, MIT, Boston, USA

  • June 8-14, 2013 Invited Chair to lead the discussion group, SAMSI, NeuroImaging Data Analysis

  • April 19, 2013 Department of Bioinformatics and Biostatistics, Emory University

  • April 12, 2013 Department of Computer Science, University of Georgia

  • March 7, 2013 Department of Statistics, University of Missouri, Columbia

  • Feb. 28, 2013 Department of Computer Science, University of Missouri, Columbia

  • Dec. 4, 2012 "LONI Presents" talk. Laboratory of Neuro Image, UCLA, USA

  • Oct. 12-14, 2012 Invited Plenary Speaker, The 4th Annual International Conference on Computational and Systems Biology (ICCSB2012), Shanghai Jiao Tong University, China

  • Sept. 27, 2012 Department of Probability and Statistics, Boston University, USA

  • July 24, 2012 Department of Computer Science, Jilin University, China

  • May 7, 2012 Bioinformatics program, UCLA, USA

  • March 16, 2012 Department of Mathematics and Statistics, Georgia State University, USA

  • March 5-7, 2012 International Conference and Exhibition on Biometrics and Biostatistics, Omaha, USA

  • June 30, 2011 The 20th Applied Statistics Symposium, New York City

  • March 11, 2011 Department of Computer Science, Institute of Bioinformatics University of Georgi. "Bayesian Inference of Complicated interactions with application of HIV drug resistance"

  • Mar 26, 2010 Department of Statistics, Chinese University of Hong Kong. "Bayesian Inference of Interactions in Biological Problems".

  • Mar 25, 2010 Li Ka Shing Institute of Health Sciences, Chinese University of Hong Kong

  • Mar 23, 2010 Department of Psychiatry, The University of Hong Kong

  • Mar 04, 2010 Department of Mathematics and Statistics, University of Massachusetts, Amherst

  • Feb 24, 2010 Department of Biostatistics, University of Minnesota

  • Feb 19, 2010 Department of Mathematical Sciences, Worcester Polytechnic Institute

  • Feb 09, 2010 Department of Statistics University of Kentucky

  • Feb 04, 2010 Department of Statistics Ohio State University

  • Feb 02, 2010 The Division of Biostatistics New York University School of Medicine

  • Jan 18, 2010 Department of Statistics, Yale University "Bayesian Inference of Interactions in Biological Problems".

  • Dec 21, 2009 Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and women's hospital, Harvard Medical school "Bayesian Models and Methods for Selecting Covariates and Interactions".

  • Dec 09, 2009 Department of Mathematics & Statistics, Mount Holyoke College

  • Sep 17, 2009 Department of Biostatistics and Bioinformatics Emory University

-the end-