Summer Student Research on the Application of Boolean Analysis

项目摘要/摘要 尽管50年来对人类结肠隐窝干细胞群体进行了广泛的研究，但我们 对维持结肠隐窝的细胞仍没有明确的定义。我们试图回答这个问题 利用新兴的单细胞RNA测序技术(scRNA-seq)，可以提供对详细信息的洞察 单个干细胞和祖细胞的转录本。我们有一种新的方法可以预测分化 应用无偏系统生物学观点和大患者衍生基因的数学模型的层次结构 表达式数据集。我们有可以预测终末分化细胞的数学模型。这个 我们使用的数学原理是基于布尔蕴涵逻辑的，而布尔蕴涵逻辑并没有被普遍应用于 研究组织细胞群体。布尔分析将一个参数(例如，基因的RNA水平)仅指定为两个 值，即高/低、1/0或正/负。应用布尔原理，可以确定 任何一对基因的表达水平之间的关系。布尔分析能够识别 人类组织和跨物种的基本基因表达关系。这样做的主要目标是 建议使用布尔隐含关系来实现对人类结肠组织的单细胞分析。基座 根据我们的初步数据，总体假设是布尔原理可以用于特定的 描述人类结肠组织中细胞类型的群体特征。本科生对这一干细胞的研究 而计算生物学研究可以让他们接触到生物医学跨学科研究的好处 并推进他们的职业生涯。

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 attempt to answer this question with emerging technology of single-cell RNA sequencing (scRNA-seq), which can provide insight into detailed transcriptomes of individual stem and progenitor cells. 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 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. 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. Applying the Boolean principle, it is possible to determine the relationship between the expression levels of any pair of genes. Boolean analysis enables identification of fundamental gene expression relationships in human tissues and across species. The primary goal of this proposal is to use Boolean implication relationships to enable single-cell analysis of human colon tissue. 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. Undergraduate involvement in this stem cell and computational biology research can expose them to the benefits of interdisciplinary research in biomedical fields and advance their professional careers.