Summer Student Research on the Application of Boolean Analysis

布尔分析应用暑期学生研究

• 批准号: 10810545
• 负责人: Debashis Sahoo
• 金额: $ 1.4万
• 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/10810545
• 关键词: Cell Differentiation process; Cells; Colon; Computational Biology; Data; Data Set; Disease; Emerging Technologies; Gene Expression; Genes; Goals; Human; Individual; Interdisciplinary Study; Investigation; Knowledge; Logic; Mathematics; Methods; Patients; Play; Population; RNA; Research; Role; Systems Biology; Tissues; career; cell type; colonic crypt; combat; human disease; human tissue; improved; insight; mathematical model; single cell analysis; single-cell RNA sequencing; stem; stem cell biology; stem cell population; stem cells; summer student; transcriptome; undergraduate student

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.

项目概要/摘要 尽管对人类结肠隐窝干细胞群的特征进行了 50 年的广泛研究，但我们 对于维持结肠隐窝的细胞仍然没有明确的定义。我们尝试回答这个问题 利用新兴的单细胞 RNA 测序 (scRNA-seq) 技术，可以深入了解详细信息 单个干细胞和祖细胞的转录组。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。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。布尔分析可以识别 人体组织和跨物种的基本基因表达关系。此次活动的首要目标 建议是使用布尔蕴涵关系来实现人类结肠组织的单细胞分析。基于 根据我们的初步数据，总体假设是布尔原理可用于具体 表征人类结肠组织中细胞类型的群体。本科生参与这种干细胞 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 领域并推进他们的职业生涯。

项目成果

Urothelial Proliferation of Unknown Malignant Potential Involving the Bladder: Histopathologic Features and Risk of Progression in De Novo Cases and Cases With Prior Neoplasia.

• DOI: 10.5858/arpa.2019-0005-oa
• 发表时间: 2020-07-01
• 期刊: Archives of pathology & laboratory medicine
• 影响因子: 4.6
• 作者: Lowenthal BM;Sahoo D;Amin MB;Hansel DE
• 通讯作者: Hansel DE

C1QA is an invariant biomarker for tissue macrophages.

C1QA 是组织巨噬细胞的不变生物标志物。

• DOI: 10.1101/2024.01.26.577475
• 发表时间: 2024
• 期刊: bioRxiv : the preprint server for biology
• 作者: Horowitz,Amir;Yu,Haocheng;Pandey,Sonalisa;Mishra,Bud;Sahoo,Debashis
• 通讯作者: Sahoo,Debashis

An AI-guided signature reveals the nature of the shared proximal pathways of host immune response in MIS-C and Kawasaki disease.

人工智能引导的特征揭示了 MIS-C 和川崎病中宿主免疫反应的共享近端通路的性质。

• DOI: 10.1101/2021.04.11.439347
• 发表时间: 2021
• 期刊: bioRxiv : the preprint server for biology
• 作者: Sahoo,Debashis;Katkar,GajananD;Shimizu,Chisato;Kim,Jihoon;Khandelwal,Soni;Tremoulet,AdrianaH;Kanegaye,John;PediatricEmergencyMedicineKawasakiDiseaseResearchGroup;Bocchini,Joseph;Das,Soumita;Burns,JaneC;Ghosh,Pradipta
• 通讯作者: Ghosh,Pradipta

Boolean implication analysis of single-cell data predicts retinal cell type markers.

• DOI: 10.1186/s12859-022-04915-4
• 发表时间: 2022-09-16
• 期刊: BMC BIOINFORMATICS
• 影响因子: 3
• 作者: Subramanian, Rohan;Sahoo, Debashis
• 通讯作者: Sahoo, Debashis

A Boolean approach for novel hypoxia-related gene discovery.

• DOI: 10.1371/journal.pone.0273524
• 发表时间: 2022
• 期刊: PloS one
• 影响因子: 3.7