Research Interests

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Nusrat Jahan's primary research area is statistical genomics. Gene expression studies are potentially useful for identifying biomarkers that can differentiate between normal and disease conditions. But these studies are characterized with small sample sizes, large number of variables, and varying study specifications. Nusrat's research focus is integrating independent expression studies originating from different platforms and tissues, but investigating similar biological conditions. She is interested in the application of weight functions to reflect lack of consistency among the significance information originating from different studies. High dimensionality is an inherent problem of genomics. Nusrat is also working on sparse sufficient dimension reduction techniques to identify linear combinations of the most important input variables (genes) that best explain the target variable prior to model building.




Publications

Publications

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Dallas Joder and Nusrat Jahan (2017), "Weighted Meta-Analysis for small sample Microarray studies," Journal of Advanced Statistics, Volume 2, No. 2, pp. 96-108. pdf

Trevor V. Adriaanse, Meshach Hopkins, Rebecca Rachan, Subodh R. Selukar, Elias Al-Najjar, Kofi P. Adragni, and Nusrat Jahan. "Statistical analysis of a case-control Alzheimer's disease: a retrospective approach with sufficient dimension reduction". Technical Report HPCF-2015-23, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2015. link

Jahan, Nusrat and Jane L. Harvill (2008), "Bispectral-based goodness-of-fit tests of Gaussianity and linearity of stationary time series," accepted for publication in Communications in Statistics: Theory and Methods. pdf

Ya, Jin; Jahan, Nusrat; Lee, Y.; Zhao, Y.; Stephenson, R. (2004)," Mathematical Modeling of Comaparative Initiation/Promotion Skin Paint Studies of B6C3F1 Mice and Swiss CD-1 Mice,"Proceedings of Hawaii International Conference on Sciences, Honolulu, HI. pdf

Jahan, Nusrat and Jane L. Harvill (2003), Goodness-of-Fit Test for Noncentral Chi-square Distribution with Unknown Noncentrality Parameter, 2003 Proceedings of American Statistical Association, Nonparametric Statistics Section, Alexandria, VA: American Statistical Association: pp1986-1990. pdf

Jahan, Nusrat and Ataharul Islam (1990), Detection of Multicollinearity and Identification of Risk Factors of Diabetes Mellitus,Journal of Dhaka University Studies, Part E (Biological Sciences), Vol. 5, No. 2, pp. 137-150. pdf