Arthritis Genomics and Bioinformatics

关节炎基因组学和生物信息学核心的总体目标是支持研究人员在 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 在整个计划中获得。核心将从关节组织中进行标准化的RNA制备， 实验动物，和扩增步骤，以产生标记的探针，从少量的体内 或体外衍生的RNA。这将有助于在整个计划中生成高度可比的数据集。 此外，核心将设计一个研究特定的"关节炎芯片"，与斑点寡核苷酸， 代表了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 与全基因组芯片相比，这在经济上是可行的， 群体之间的兼容性。核心的生物信息学人员，他们已经获得了重要的 在微阵列分析的经验，将指导，培训，并帮助研究人员通过数据分析在一个开放的 合作的方式。核心将提供对基本分析包的访问，以及编写 以数据驱动的方式定制软件，以应对特定的实验情况。此外，本发明还提供了一种方法， 数据分析将受益于关节炎期间基因表达的微阵列数据的基线。中央 用于安全数据存储的服务器将存放数据副本，用于数据浏览的基于Web的软件将 作为特定于计划的内联网使用，并酌情用于公开发布。此外，核心将 对收集的数据进行数据挖掘，通过协调处理进行探索 和数据的存储，以及我们预先存在的关于关节炎关节中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-基因相关性和聚类。 条件，并将产生功能基因层次结构。这些荟萃分析将丰富每一个 个体分析：定义，例如，尽管基因突变，但仍被诱导的基因子集。 关节炎的阻断将有助于查明该基因所涉及的细胞或功能水平。在 此外，通过合并和协调的数据集进行的荟萃分析也将提供 对"关节炎基因组"的独特见解。

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".