Data Management and Bioinformatics Core

摘要 数据管理和生物信息学核心(DMBC)将支持每个项目和总体目标 通过应用多种类型的计算分析来确定小说的功能作用 免疫调节剂。这项工作将包括：(I)处理和执行大型- 在项目和核心内产生的规模数据集；(2)确定基因、蛋白质、表观遗传学 受免疫干扰影响最大的修饰和组织表型；以及(Iii)通过整合 识别相关共表达模块和推断关键字的内部生成和公开可用的数据集 免疫表型的基础调节者。充分利用诸如RNA-SEQ的高通量技术， CHIP-SEQ和ATAC-SEQ以及多参数分子表型(CyTOF、MIBI、CODEX)需要 重要的基础设施和复杂的分析方法。DMBC在以下方面拥有深厚的专业知识 由这些技术产生的数据，并开发了计算工具来发现新的免疫 监管机构，并确定其行动机制。此外，DMBC拥有必要的资源来 管理和分析这些大型数据集，并将它们分发给计划调查人员和 通过网站和现有的公共数据库公开。 核心为信息学核心开发了一个经过验证的模型，在该模型中，个人计算 调查人员被嵌入到每个项目中。这种结构的优点是 计算生物学家可以参与实验计划的各个层面。核心发现了这一点 结构特别有效，因为在各个中心使用的方法范围广泛，各不相同 (系统生物学、遗传学、多参数信号分析)。

Summary The Data Management and Bioinformatics Core (DMBC) will support each of the Projects and the overall goals of the program by applying multiple types of computational analyses to determine the functional role of novel immune regulators. This work will include: (i) processing and performing bioinformatics analysis of the large- scale data sets generated within the Projects and Cores; (ii) identifying genes, proteins, epigenetic modifications and tissue phenotypes that are most affected by immune perturbations; and (iii) by integrating internally generated and publicly available data sets to identify relevant co-expression modules and infer key regulators underlying immune phenotypes. Fully exploiting high throughput technologies such as RNA-seq, ChIP-seq and ATAC-seq, as well as multi-parameter molecular phenotyping (CyTOF, MIBI, CODEX) requires significant infrastructure and sophisticated analysis methods. The DMBC has deep expertise in the analysis of data generated by these technologies and has developed computational tools to discover novel immune regulators and determine their mechanisms of action. Furthermore, the DMBC has necessary resources to manage and analyze these large data sets and disseminate them to the program investigators and to the public via websites and existing public databases. The Core has developed a proven model for the informatics core in which individual computational investigators are imbedded within each of the projects. The advantage of this structure is that the computational biologists can participate at every level of the experimental program. The Core has found this structure to be particularly effective given the broad range of approaches used disparate at the various centers (systems biology, genetics, multi-parameter signaling analysis).