Arthritis Genomics and Bioinformatics

关节炎基因组学和生物信息学核心的总体目标将是支持 利用微阵列技术的程序。核心将提供统一的样品制备、微阵列 设计、数据存储和生物信息学，从而最大限度地提高信息的可靠性和兼容性 通过该计划获得。核心将进行标准化的核糖核酸制备从关节组织 实验动物，以及从体内少量DNA合成标记探针的扩增步骤 或体外衍生的RNA。这应有助于在整个项目中生成高度可比的数据集。 此外，Core还将设计一种特定于研究的“关节炎芯片”，它带有斑点寡核苷酸，可以 代表在关节形成过程中发生变化的基因。这些定制芯片将提供灵活性，允许更大的 吞吐量超过全基因组芯片在经济上可行的水平，并再次增强数据 两个组之间的兼容性。核心的生物信息学人员，他们已经获得了重要的 在基因芯片分析方面的经验，将指导、培训和帮助调查人员在公开的环境中进行数据分析 和协作的态度。核心将提供对基本分析包的访问，并能够编写 以数据驱动的方式定制软件，以响应特定的实验情况。此外, 数据分析将受益于关于关节炎期间基因表达的微阵列数据的基线。一个中环 用于安全数据存储的服务器将存放数据的副本，用于数据浏览的基于Web的软件将 适用于特定于计划的内部网，并酌情用于公开张贴。此外，核心将 对收集到的数据进行数据挖掘，协同处理使探索成为可能 和数据的存储，以及我们先前存在的关于关节炎关节基因表达进化的数据。 交叉实验分析将在各种不同的基因中寻找基因-基因的相关性和聚类 条件，并将产生功能基因层级。这些元分析将丰富每一个 个体分析：例如，定义尽管基因突变仍被诱导的基因子集 阻断关节炎将有助于精确定位该基因所涉及的细胞或功能水平。在……里面 此外，由合并和协调的数据集实现的荟萃分析也将提供 对“关节炎基因组”的独特洞察力。

The overall goal of the Arthritis Genomics and Bioinformatics Core will be to support investigators in the Program utilizing microarray techniques. The core will provide uniform sample preparation, microarray design, data storage and bioinformatics, thus maximizing the reliability and compatibility of information obtained across the Program. The Core will perform standardized RNA preparation from joint tissues of experimental animals, and the amplification steps to generate labeled probe from small amounts of in vivo or in vitro derived RNA. This should help to generate highly comparable datasets throughout the Program. In addition, the Core will design a study-specific "Arthritis Chip", with spotted oligonucleotides that represent genes that vary during arthritogenesis. These custom chips will provide flexibility, allow a greater throughput than would be economically feasible with whole-genome chips, and again enhance data compatibility between the groups. The Core's bioinformatics personnel, which have acquired significant experience in microarray analysis, will guide, train, and help investigators through data analysis in an open and collaborative manner. The Core will provide access to basic analysis packages, and the ability to write custom software in a data-driven manner, in response to particular experimental situations. In addition, data analysis will benefit from a baseline of microarray data on gene expression during arthritis. A central server for secure data storage will house copies of the data, and Web-based software for data browsing will be applied as a Program-specific intranet and for public posting, as appropriate. In addition, the Core will perform data mining on the assembled data, explorations made possible by the coordinated processing and storage of the data, and by our pre-existing data on the evolution of gene expression in arthritic joints. Cross-experiment analyses will search for gene-gene correlations and clusters throughout a variety of conditions, and will generate functional gene hierarchies. These meta-analyses will enrich each of the individual analyses: defining, for example, the subset of genes that are still induced in spite of a genetic blockade of arthritis will help to pinpoint the cellular or functional level at which the gene is implicated. In addition, the meta-analyses made possible by the combined and coordinated datasets will also provide a unique insight into the "arthritis genome".