Bioinformatics Core

生物信息学核心位于计算和综合生物学中心（CCIB）， 马萨诸塞州总医院，以及麻省理工学院和哈佛的布罗德研究所。核心拥有专业知识， 大规模数据集的分析和促进综合系统生物学方法。具体目标 MGH/哈佛AADCRC计划中的生物信息学核心是提供必要的专业知识： 1)分析项目1、2和3中生成的基因表达数据，并确定转录模式 在临床相关的表型状态，以确定特定环境的生物网络和途径 这些国家的基础模块。对于项目1，将进行比较表达谱分析， 变应性哮喘患者变应原特异性与大量CD 4 [+] T细胞的差异表达基因 与过敏性非哮喘患者相比。对于项目2，纵向表达分析将在 口服免疫疗法中的多种CD 4 [+] T细胞亚群。对于项目3，差异表达将是 在刺激条件和时间点上检查四个DC亚群中的每一个（朝向 变成致耐受性的DC），然后在每个刺激条件和时间点的DC亚群中。 还将对暴露于itDC后的T细胞亚群进行类似的分析。一些 分析方法将酌情采用，其中包括动态因素分析、 析因设计或最近邻（相关）分析。2)将核心表达式签名定义为 促进NanoString代码集的开发，用于进一步的高度多重定量表达 分析和前瞻性数据收集。3)集成多种数据类型以促进“系统范围” 认识在各自的比较中鉴定的差异表达基因的簇将被 检查功能基因组的富集，例如与生物过程相关的那些， 途径。生物信息学核心将确定与通路相关的网络模块，并建立功能性的 丰富的地图，以指导实验重点调查复杂的分子机制 支持哮喘、过敏性疾病和过敏原特异性耐受诱导。的整合 从多个来源询问的正交数据，包括蛋白质-蛋白质相互作用，转录因子结合， 数据和其他公开可用的表达数据集将使我们能够扩展我们的分析， 关于调节电路、信号网络和通路结构的额外的“系统范围”的见解 参与哮喘和食物过敏的发病机制。

The Bioinformatics Core is located in the Center for Computational and Integrative Biology (CCIB) at Massachusetts General Hospital, and at the Broad Institute of MIT and Harvard. The core has expertise in the analysis of large-scale datasets and facilitates integrative systems biology approaches. The specific aims of the Bioinformatics Core in the MGH/Harvard AADCRC Program are to provide the necessary expertise: 1) To analyze gene expression data generated in Projects 1, 2 and 3 and determine transcriptional patterns across clinically relevant phenotypic states to identify context-specific biological networks and pathway modules underlying these states. For project 1, comparative expression profiling will be conducted to identify differentially expressed genes between allergen-specific versus bulk CD4[+] T cells in allergic asthmatics versus allergic non-asthmatics. For project 2, longitudinal expression analysis will be performed across multiple CD4[+] T cell subsets during oral immunotherapy. For project 3, differential expression will be examined across stimulation conditions and time-points for each of the four DC subpopulations (towards becoming tolerogenic itDC), and then across the DC subpopulations for each stimulation condition and time-point. A similar analysis will also be conducted for T cell subsets following exposure to itDCs. A number of analytical methods will be implemented as appropriate, and these include dynamic factor analysis, analysis of factorial design or nearest neighborhood (correlation) analysis. 2) To define core expression signatures to facilitate the development of NanoString code sets for further highly multiplexed quantitative expression analyses and prospective data collection. 3) To integrate multiple data types to facilitate a 'systems-wide' understanding. Clusters of differentially expressed genes identified in the respective comparisons will be examined for enrichment of functional gene sets such as those associated with biological processes and pathways. The Bioinformatics Core will identify pathway-associated network modules and build functional enrichment maps to guide experimentally focused investigations into the complex molecular mechanisms underpinning asthma, allergic diseases and allergen-specific tolerance induction. The integration of orthogonal data interrogated from multiple sources, including protein-protein interactions, transcription factor-binding data and other publicly available expression datasets will allow us to extend our analysis to gain additional 'systems-wide' insights about the structure of regulatory circuits, signaling networks and pathways involved in the pathogenesis of asthma and food allergy.