基本情况

张顺普，内布拉斯加林肯大学终身正教授，兼任美国国家癌症研究所高级数理统计师。

研究领域

生物信息处理、信号处理、多重检验等领域等

主要经历

2010年至今高级数理统计师，美国国家癌症研究所

2009年至今终身正教授，内布拉斯加林肯大学

2004年至2009年终身副教授，内布拉斯加林肯大学

1997年至2004年终身副教授，美国阿拉斯加费尔班克斯大学

论文发表


  1. Wei, L. and Zhang, S. (1995). The convergence rates of empirical Bayes estimation in a multiple linear regression model. Annals of the Institute of Statistical Mathematics, No. 1, Vol 47, 81-97
  2. Karunamuni, R.J. and Zhang, S. (1996). Empirical Bayes detection of a change in distribution. Annals of the Institute of Statistical Mathematics, No. 4, Vol 48, 229-246
  3. Zhang, S. and Karunamuni, R.J. (1997). Bayes and empirical Bayes estimation with errors in variables. Statistics and Probability Letters, 33, 23-34
  4. Zhang, S. and Karunamuni, R.J. (1998). On kernel density estimation near endpoints. Journal of Statistical Planning and inference, 70, 301-316
  5. Zhang, S., Karunamuni, R.J. and Jones, M.C. (1999). An improved estimator of the density function at the boundary. Journal of the American Statistical Association, 94, 1231-1241
  6. Zhang, S. and Karunamuni, R.J. (2000). On nonparametric density estimation at the boundary. Journal of Nonparametric Statistics, 12, 197-221
  7. Zhang, S. and Karunamuni, R.J. (2000). Boundary Bias Correction for Nonparametric Deconvolution. Annals of the Institute of Statistical Mathematics, 52, 4, 612-629
  8. Karunamuni, R.J., Singh, R.S. and Zhang, S. (2002). Empirical Bayes estimation for the location family. Journal of Nonparametric Statistics, 14(4), 435-448
  9. Wang, J., Ikeda, M., Zhang, S., and Gerdes, G. (2005). Linking the northern hemisphere sea ice reduction trend and the quasi-decadal Arctic sea ice oscillation. Climate Dyn., 24, 115-130
  10. Zhang, S. (2006). An Improved Nonparametric Approach for Detecting Differentially Expressed Genes with Replicated Microarray Data. Statistical Applications in Genetics and Molecular Biology 5.1
  11. Zhang, S. (2007). A comprehensive evaluation of SAM, the SAM R-package and a simple modification to improve its performance. BMC Bioinformatics, 8:230
  12. Zhang, S., Lu, G., Fang, X., and Donis, R. (2007). Multidimensional scaling and model-based clustering analyses for the clade assignments of the HPAI H5N1 viruses. Options for the Control of Influenza VI, International Medical Press. London: Blackwell
  13. Jiao, S. and Zhang, S. (2008). The t-mixture model approach for detecting differentially expressed genes in microarrays. Functional & Integrative Genomics, 8: 181-186
  14. Lu, G., Zhang, S., and Fang, X. (2008). An improved string composition method for sequence comparison. BMC Bioinformatics, 9 (Suppl 6): S15
  15. Jiao, S. and Zhang, S. (2008). On correcting the overestimation of the permutation-based false discovery rate estimator. Bioinformatics, 24(15):1655-1661
  16. Wang, Y., Eskridge, K. M., and Zhang, S. (2008). Semiparametric mixed analysis on PK/PD Models using differential equations. Journal of Pharmacokinetics and Pharmacodynamics, 35(4): 443-63
  17. Zhang, S. and Karunamuni, R.J. (2009). Deconvolution Boundary Kernel Method in Nonparametric Density Estimation. Journal of Statistical Planning and Inference, 139, 2269-2283
  18. Zhang, S. (2009). The split sample permutation t-tests. Journals of Statistical Planning and Inferences, 39 (10), 3512-3524
  19. Zhang, S. (2009). On Parametric Estimation of Population Abundance for Line a Transect Sampling. Environmental and Ecological Statistics. 18 (1), 79-92
  20. Jiao, S. and Zhang, S. (2010). Estimating the proportion of equivalently expressed a) genes in microarray data based on transformed test statistics. Journal of b) Computational Biology. 17 (2), 177-87
  21. Mechanic, L. E., Chen, H-S., Amos, C. I. Chatterjee, N., Cox, N. J., Divi, R. L., Fan, R., Harris, E. L., Jacobs, K., Kraft, P., Leal, S. M., McAllister, K, Moore, J. H., Paltoo, D. N., Province, M. A., Ramos, E. M., Ritchie, M. D., Roeder, K., Schaid, D. J., Stephens, M., Thomas, D. C., Weinberg, C. R., Witte, J., Zhang, S., Zöllner, S., Feuer, E, J., Gillanders, E. M. (2011). Next Generation Analytic Tools for Large Scale Genetic Epidemiology Studies of Complex Diseases. Genetic Epidemiology. 36: 22–35


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