Summer Student Research on the Application of Boolean Analysis

项目总结/摘要 尽管50年来对人类结肠隐窝中干细胞群体的特征进行了广泛的研究， 仍然没有一个明确的定义细胞，维持结肠隐窝。我们有一种新方法 预测分化层次使用无偏系统生物学的观点和数学模型的大 患者来源的基因表达数据集。我们有数学模型可以预测 分化细胞我们使用的数学原理是基于布尔蕴涵逻辑， 通常用于研究组织细胞群。布尔分析分配参数（例如RNA水平 一个基因）只有两个值，即，高/低、1/0或正/负。该提案的主要目标是 使用布尔蕴涵关系来解码人类结肠的组织结构。基于我们 初步数据的总体假设是，布尔原理可以用来具体表征 人类结肠组织中的细胞类型的群体。在这个建议中，我们正在培训一名本科生， 在研究环境中进行数据分析。这些研究有望产生关于细胞的信息， 分化、诊断和预后生物标志物。因此，它们有可能影响 本科生的职业生涯。

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.