Computational systems immunology core

计算系统免疫学核心

基本信息

批准号：
10427144
负责人：
Soumya Raychaudhuri
金额：
$ 49.84万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-06-15 至 2026-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10427144
关键词：
Algorithms Architecture B-Lymphocytes Cell Communication Cells Cellular Structures Clonal Expansion Complex Computational Biology Data Data Analytics Data Science Data Set Development Discriminant Analysis Disease Event Fibroblasts Gene Expression Genetic Transcription Genomic approach Goals Heterogeneity Hospitals Human Resources Image Image Analysis Immune Immunology Individual Institutes Laboratories Lead Lesion Manuals Medical Methods Morphologic artifacts National Institute of Allergy and Infectious Disease National Institute of Arthritis and Musculoskeletal and Skin Diseases Physiological Population Positioning Attribute Program Research Project Grants Protocols documentation Research Rheumatism Rheumatoid Arthritis Sampling Series Structure System Systemic Lupus Erythematosus Systems Biology T-Lymphocyte Techniques Technology Testing Time Tissue Stains Tissues Training Tuberculosis Woman autoimmune rheumatologic disease base cell type deep learning experience experimental study high dimensionality image processing imaging platform insight large scale data machine learning classifier medical schools monocyte multidimensional data programs single cell analysis single-cell RNA sequencing success transcriptome sequencing trend

项目摘要

Abstract The three research projects of this program project grant utilize single cell genomic strategies and complementary imaging strategies to define cell-cell interactions in target tissues in systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). These projects will be used to develop insight into the development, function, localization, and interactions of B and T lymphocytes (Project 1), monocytes (Project 2), and fibroblasts (Project 3). Key to understanding these cell-types is the effective interpretation of complex high- dimensional data sets. The Computational Systems Immunology (CSI) core will support the analytical and computational needs for the three projects. This core will build from our experience with the Accelerating Medical Partnerships (AMP) RA/SLE program where analysis of high dimensional single cell data sets has now given us the first look at the constituent immune and stromal cellular populations. CSI will 1) employ computational strategies to analyze and integrate multiple single cell RNA-seq datasets to define key cellular populations 2) use trajectory analysis to define transitional states between cells. 3) Define clonal populations with repertoire sequencing and 4) Define the relationship between cell-cell interactions and transcriptional states. The CSI is uniquely positioned to analyze and integrate RA and SLE data with its long-standing expertise in rheumatic diseases, systems biology, and imaging analysis.

抽象的该计划项目的三个研究项目利用单细胞基因组策略和互补的成像策略以定义全身性狼疮目标组织中细胞细胞相互作用红斑（SLE）和类风湿关节炎（RA）。这些项目将用于发展对 B和T淋巴细胞的开发，功能，定位和相互作用（项目1），单核细胞（项目2），和成纤维细胞（项目3）。了解这些细胞类型的关键是对复杂高级的有效解释维数据集。计算系统免疫学（CSI）核心将支持分析和这三个项目的计算需求。这个核心将源于我们的加速经验医疗合作伙伴关系（AMP）RA/SLE计划，其中高维单细胞数据集的分析现已给了我们首次查看组成型免疫和基质细胞种群。 CSI将1）雇用分析和集成多个单细胞RNA-seq数据集以定义关键细胞的计算策略种群2）使用轨迹分析来定义细胞之间的过渡状态。 3）定义克隆人群使用曲目测序和4）定义细胞 - 细胞相互作用与转录之间的关系国家。 CSI的独特位置可以分析和整合RA和SLE数据与长期存在风湿病，系统生物学和成像分析方面的专业知识。