Bioinformatics Core

生物信息学核心

基本信息

批准号：
9111873
负责人：
Leonard McMillan
金额：
$ 15.66万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至 2017-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9111873
关键词：
Animal Model Animals Antiviral Therapy Bioinformatics Biological Response Modifiers Brain Cells Collaborations Communication Communities Complex Data Data Analyses Data Quality Data Storage and Retrieval Databases Development Ensure Fostering Gene Expression Gene Proteins Genes Genome Grant Housing Human Resources Immune Immune response Immunogenetics Infection Instruction Laboratories Link Management Information Systems Maps Modeling Molecular Molecular Profiling Mus Pathway Analysis Pathway interactions Phase Phenotype Predisposition Process Proteomics Protocols documentation Quality Control Quantitative Trait Loci RNA RNA Processing Reading Research Research Infrastructure Research Personnel Research Project Grants Resources Sampling Secure Spleen Statistical Data Interpretation Structure of parenchyma of lung System Systems Biology Untranslated RNA Vaccines Validation Virus Diseases Work biodefense cell type computer infrastructure computerized data processing data management experience flexibility genetic analysis genetic pedigree high throughput analysis improved information processing insight lymph nodes next generation sequencing pathogen programs research study tool trait validation studies web portal

项目摘要

PROJECT SUMMARY (See instructions): The Bioinformatics Core provides data management, communications systems, statistical analysis, and support for functional interpretation of high-throughput data as part of the systems biology approach to immunogenetics. Existing platforms will be leveraged to develop and maintain a sophisticated laboratory information management system (LIMS) to facilitate the tracking of information, the processing of raw data through computational pipelines, and communication between all U19 investigators. In addition, the Core will support the prioritization of key immune genes and pathways derived from expression quantitative trait loci (eQTL) and QTL analyses. The Specific Aims of the Core are as follows: Aim 1: Develop and maintain a dedicated data management system with a Systems Immunogenetics Web Portal. The Core will define and implement a program-wide data communication plan that ensures the capture of all grant-generated sample information, data, and resources. Public access to grant-generated data, resources, and mouse line infomnation will also be provided through the Web portal. Aim 2; Assist in the development of data processing pipelines that ensure data is high-quality, conforms to technical specifications for modeling, and is accessible to all U19 investigators. In collaboration with the Systems Immunogenetics Core, an existing infrastructure will be leveraged to develop and implement data processing pipelines for all high-throughput profiling data, including quality control protocols for microarray, next-generation sequencing, and proteomics. Aim 3: Provide analytical support for high-throughput data and the computational predictions generated by the Research Projects and Cores. Statistical, computational, and functional analysis support will be provided for the interpretation of data and results. In addition, the Core will provide analysis of next-generation sequencing data, including in-depth analysis of noncoding RNAs, and processing and interpretation of targeted proteomics studies allowing for a systems level view of key immune genes and pathways across a select set of mouse lines.

项目摘要（请参阅说明）：生物信息学核心提供数据管理，通信系统，统计分析以及对高通量数据的功能解释的支持，这是系统生物学方法的一部分。现有平台将被利用以开发和维护复杂的实验室信息管理系统（LIMS），以促进信息跟踪，通过计算管道来处理原始数据以及所有U19研究人员之间的通信。此外，核心将支持关键免疫基因和从表达定量性状基因座（EQTL）和QTL分析得出的途径的优先级。核心的具体目的如下：AIM 1：使用系统免疫原料Web门户开发和维护专用数据管理系统。核心将定义和实施整个程序范围的数据通信计划，以确保捕获所有赠款生成的示例信息，数据和资源。公众访问授予生成的数据，资源和鼠标线信息也将通过Web门户提供。目标2；协助开发数据处理管道，以确保数据是高质量的，符合建模的技术规格，并且所有U19研究人员都可以使用。与系统免疫遗传学核心合作，将利用现有的基础架构来开发和实施所有高通量分析数据的数据处理管道，包括用于微阵列的质量控制协议，下一代测序和蛋白质组学。目标3：为高通量数据和研究项目和核心产生的计算预测提供分析支持。将提供统计，计算和功能分析支持，以解释数据和结果。此外，核心将提供下一代测序数据的分析，包括对非编码RNA的深入分析，以及对靶向蛋白质组学研究的处理和解释，从而允许对关键免疫基因和一组小鼠系的系统级别视图。