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.