Mayetri Gupta: selected publications

  • Gupta, M. (2007). Generalized hierarchical Markov models for discovery of length-constrained sequence features from genome tiling arrays. Biometrics, in press.

  • Gupta, M. and Ibrahim, J. G. (2007). Variable selection in regression mixture modeling for the discovery of gene regulatory networks. Journal of the American Statistical Association, in press.

  • Gupta, M., Qu, P. and Ibrahim, J. G. (2007). A temporal hidden Markov regression model for the analysis of gene regulatory networks. Biostatistics, in press.

  • Giresi, P. G., Gupta, M. and Lieb, J. D. (2006). Regulation of nucleosome stability as a mediator of chromatin function. Curr. Opin. Genet. Dev. 16 (2): 171-176.

  • Gupta, M. and Liu, J. S. (2006). Bayesian modeling and inference for motif discovery. Bayesian inference for gene expression and proteomics. Do et al., (eds.). Cambridge University Press.

  • Gelfond, J. L. and Gupta, M. (2006). Bayesian models for motif discovery from ChIP-chip and sequence data. International Society for Bayesian Analysis Bulletin 13 (4): 2-4.

  • Maki, A., Kono, H., Gupta, M. , Asakawa, M., Suzuki, T., Matsuda, M., Fujii, H., Rusyn, I. (2006). Predictive power of biomarkers of oxidative stress and inflammation in patients with hepatitis C virus-associated hepatocellular carcinoma. Annals of Surgical Oncology 14:1182-1190.

  • Gupta, M. and Liu, J. S. (2005). De-novo cis-regulatory module elicitation for eukaryotic genomes. Proceedings of the National Academy of Sciences, U. S. A. 102 (20): 7079-7084. Software

  • Gupta, M. and Liu, J. S. (2003). Discovery of conserved sequence patterns using a stochastic dictionary model. Journal of the American Statistical Association 98 (461), 55-66. Software

  • Liu, J. S., Gupta, M., Liu, X. L. and Lawrence, C. L.(2002). Statistical models for motif discovery. (with discussion) Case Studies in Bayesian Statistics, Vol. 6, Springer-Verlag, New York.



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