Immunogenomics and Systems Biology Core

免疫基因组学和系统生物学核心

基本信息

批准号：
10452138
负责人：
Johann Eli Gudjonsson
金额：
$ 30万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-03-18 至 2026-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10452138
关键词：
ATAC-seq Address Antigen-Antibody Complex Atopic Dermatitis Autoimmune Diseases Autoimmune Process Basic Science Binding Biological Assay Biological Markers Biological Process Biology CD8B1 gene Cells Chromosome Mapping Clinical Clinical Data Clinical Investigator Computer Models Computer software Computing Methodologies Consultations Custom Data Data Analyses Data Analytics Data Set Development Disease Epigenetic Process Fibroblasts Functional disorder Funding Generations Genetic Genetic Variation Genomic approach Genomics Goals Heterogeneity Immune Immune System Diseases Immunogenomics Inflammatory Institutes Intervention Link Lupus Maps Mediating Michigan Modality Modeling Molecular Molecular Disease Molecular Profiling Multiomic Data Pathogenesis Pathogenicity Performance Population Process Psoriasis Psoriatic Arthritis Research Research Personnel Resources Role Shapes Signal Transduction Skin Standardization Statistical Models System Systemic Lupus Erythematosus Systems Biology Technology Therapeutic Intervention Training Translations Universities advanced analytics base cell type computerized data processing cytokine data analysis pipeline data curation data integration data management data standards disease heterogeneity epigenomics experience flexibility genetic approach genetic information genomic data high throughput screening innovation insight keratinocyte multiple data types multiple omics novel open source tool programs ranpirnase response sample collection structured data transcription factor transcriptome sequencing transcriptomics translational scientist treatment response

项目摘要

ABSTRACT The Immunogenomics and Systems Biology Core (ISCB) at University of Michigan will support the data analytics, management, and disease translation to meet the goals of the entire AMP AIM Network. The ISCB will be based on our extensive experience in the development of genetics and systems biology approaches, working with a broad range of multi-omics data including genetic, epigenetic, single-cell and spatial-seq data, to increase our understanding of the factors that contribute to disease pathogenesis and heterogeneity. The premise of our approach is that integrating genetic information with other -omic data, collected through the AMP AIM Network, will facilitate and accelerate discovery of critical pathogenic mechanisms and help unravel the biologic processes contributing to disease heterogeneity. This approach will utilize advanced analytical approaches in causal mechanism inference, modeling and single cell and spatial genomics data integration. To achieve this we will i) deploy highly customized, scalable, and robust data processing capabilities and standardized pipelines for curation, processing, management, and sharing of multi-omics and integrated clinical datasets; ii) build comprehensive disease specific roadmaps, and define shared and unique molecular mechanisms of AMP AIM target diseases utilizing statistical genetics and genomics approaches; iii) identify, characterize, and refine biomarkers shaping disease heterogeneity and intervention response by integrating multi-omics and clinical data through statistical and computational modeling.

抽象的密歇根大学的免疫基因组学和系统生物学核心（ISCB）将支持数据分析，管理和疾病翻译，以满足整个 AMP AIM 网络的目标。 ISCB 将设在基于我们在遗传学和系统生物学方法开发方面的丰富经验，与广泛的多组学数据，包括遗传、表观遗传、单细胞和空间序列数据，以提高我们的研究能力了解导致疾病发病机制和异质性的因素。我们的前提方法是将遗传信息与通过 AMP AIM 网络收集的其他组学数据相整合，将促进和加速关键致病机制的发现，并帮助揭示生物过程导致疾病异质性。该方法将利用先进的因果分析方法机制推理、建模以及单细胞和空间基因组学数据集成。为了实现这一目标，我们将 i) 部署高度定制、可扩展且强大的数据处理能力和标准化管道多组学和综合临床数据集的策划、处理、管理和共享； ii) 构建全面的疾病特定路线图，并定义 AMP AIM 共享和独特的分子机制利用统计遗传学和基因组学方法针对疾病； iii) 识别、表征和完善通过整合多组学和临床数据来塑造疾病异质性和干预反应的生物标志物通过统计和计算模型。