Summer Student Research on the Application of Boolean Analysis

项目总结/文摘

Project Summary/Abstract Despite 50 years of extensive investigations to characterize the stem cell population in human colon crypts, we still do not have a clear definition of cells that maintain the colon crypts. We have a new method that can predict differentiation hierarchy using unbiased systems biology perspective and mathematical models of large patient-derived gene expression datasets. We have mathematical models that can predict the terminally differentiated cells. The mathematical principle we use is based on Boolean implication logic that has not been commonly applied to study tissue cell populations. The Boolean analysis assigns a parameter (e.g. RNA level of a gene) with only two values, i.e., high/low , 1/0, or positive/negative. The primary goal of this proposal is to use Boolean implication relationships to decode the tissue organization of human colon. Based on our preliminary data the overall hypothesis is that Boolean principles can be used to specifically characterize the population of cell types in human colon tissue. In this proposal we are training an undergraduate student to perform data analysis in a research setting. These studies are expected to yield information about cell differentiation, diagnostic and prognostic biomarkers. Consequently, they have the potential to impact professional careers of the undergraduate student.