Boolean Analysis on RT-PCR data

RT-PCR 数据的布尔分析

• 批准号: 10799309
• 负责人: Debashis Sahoo
• 金额: $ 22.5万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10799309
• 关键词: ALCAM gene; Area; B-Lymphocytes; Bioinformatics; Biological Process; Bladder; CDX2 gene; Cell Differentiation process; Cells; Clinical; Colon; Computer Analysis; Data; Data Set; Development; Developmental Biology; Disease; Enterocytes; Enteroendocrine Cell; Epithelium; Fingers; Funding; Future; Gastrointestinal Diseases; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Goals; Goblet Cells; Guidelines; Human; Individual; Injury; Knowledge; Logic; Mathematics; Methods; Mucous body substance; Mus; Organoids; Patients; Play; Population; Prognostic Marker; Prostate; RNA; Request for Proposals; Research; Reverse Transcriptase Polymerase Chain Reaction; Role; Sampling; Structure; System; Systems Biology; Time; Tissue Differentiation; Tissue Sample; Tissues; Validation; Work; adult stem cell; base; cell type; colonic crypt; crypt cell; diagnostic biomarker; equipment acquisition; human disease; human tissue; improved; insight; mathematical model; novel; prevent; repaired; self-renewal; spatiotemporal; stem; stem cells; therapeutic target; tool

Project Summary/Abstract Colon crypt stem cells are characterized by their ability to self-renew, or divide and produce more stem cells, as well as their ability to differentiate into various specialized cell types, such as absorptive cells, goblet cells, and enteroendocrine cells, that make up the colon lining. Abnormalities in colon crypt stem cells can lead to the development of many human gastrointestinal diseases. 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 requesting availability of funds for a single equipment purchase of Bio-Rad CFX Opus Real-time PCR System that will significantly improve gene expression analysis for validation. These studies are expected to yield information about cell differentiation, diagnostic and prognostic biomarkers. Consequently, they have the potential to impact current guidelines about how to treat and manage human diseases and even help identify potential future therapeutic targets.

项目概要/摘要 结肠隐窝干细胞的特点是具有自我更新或分裂并产生更多干细胞的能力，如 以及它们分化成各种特殊细胞类型的能力，例如吸收细胞、杯状细胞和 肠内分泌细胞，构成结肠内壁。结肠隐窝干细胞的异常可能导致 许多人类胃肠道疾病的发生。我们有一种可以预测分化的新方法 使用无偏见的系统生物学视角和大型患者来源基因的数学模型进行层次结构 表达数据集。我们有可以预测终末分化细胞的数学模型。这 我们使用的数学原理是基于布尔蕴涵逻辑，但尚未普遍应用于 研究组织细胞群。布尔分析仅用两个参数指定一个参数（例如基因的 RNA 水平） 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。根据我们的初步数据 假设布尔原理可以用来具体描述细胞类型的群体 人类结肠组织。在此提案中，我们要求提供资金用于购买单一设备 Bio-Rad CFX Opus 实时 PCR 系统将显着改进基因表达分析以进行验证。 这些研究预计将产生有关细胞分化、诊断和预后生物标志物的信息。 因此，它们有可能影响当前有关如何治疗和管理人类的指南 疾病，甚至有助于确定未来潜在的治疗目标。