Although every cell in the human body has nearly the same DNA sequence, there are many different cell types performing different functions; for example, lymphoblast cells which differentiate into white blood cells or endothelial cells which provide a lining throughout the human vascular system. But cells do not always function as they should, for example, overproduction of white blood cells can be caused by lymphoblastic leukemia, a type of cancer. I intend to use data on the sensitivity of parts of the genome to deoxyribonuclease (DNase) digestion to explain the differences in cell behavior. Regions of the genome structure that are hypersensitive to DNase have already been shown to affect gene expression. I want to determine if portions of the genome which are mildly sensitive, or mesosensitive, to DNase play a role in cell differentiation. My hypothesis is that DNase can identify large scale regions, on the order of thousands of base pairs, that harbor cell type specific genes. I used Segway, software which uses a dynamic Bayesian network, to segment the genome based on DNase sensitivity data into regions of low sensitivity, mesosensitivity, and hypersensitivity on six different cell types. From my segmentations I removed the hypersensitive regions from considerations, and compared the low and mesosensitive regions to gene expression data. I found that regions Segway labels mesosensitive had higher levels of expression than low sensitivity regions. I expect to find that many of the regions responsible for cell type specific behavior are mesosensitive. If this is the case, I hope the results will be robust enough such that anyone with access to DNase data can determine what genes are active in a population of cells, enabling them to better predict the behavior of the cells. In furthering our understanding of gene regulation, we may better understand diseases such as leukemia.