Core--Biomedical Informatics

研究生物分子对Ahr配体的反应的综合方法需要 现代基因组学和蛋白质组学工具的应用。通过使用这些工具，各个项目将 生成大量数据，必须对这些数据进行管理、存储、分析和挖掘， 从大量的信息中获取知识。生物医学信息学核心（BIG）的形成是为了执行 这些功能。BIC的主要使命是使生物医学研究人员能够得出最佳的 以最有效的方式使用基因组和蛋白质组数据。为了实现这一目标，将军 BIC的理念是数据解释的责任应由个人承担 研究人员是他们所研究的生物系统的专家。我们 核心职责是提供一致的初步数据分析、软件工具、数据管理 基础设施和培训是他们成功的必要条件。这一使命将通过 以下具体目标：（1）开发管理和存储微阵列所需的基础设施， 串联亲和纯化（TAP）数据;（2）进行生物医学微阵列数据分析 调查人员，并提供商业和定制的软件工具，用于可视化和分析 微阵列和TAP数据;（3）为所有生物医学研究人员提供培训和支持， 软件工具的应用和利用与其具体分析需求有关。对于大多数人来说， 基因组学和蛋白质组学研究中存在的复杂数据集，个体的视觉和直观能力， 研究人员必须与计算分析相结合，以便识别出 数据建立BIC将确保所有基因表达和TAP数据的中央储存库， 将使有效的数据挖掘发生在项目内和跨项目。

An integrated approach for investigating the biomolecular responses to Ahr ligands necessitates the application of modern genomic and proteomic tools. By utilizing these tools, the individual projects will be generating significant amounts of data that must be managed, stored, analyzed, and mined in order to derive knowledge from the mass of information. The Biomedical Informatics Core (BIG) was formed to perform these functions. The primary mission of the BIC is to enable the biomedical investigators to derive optimal use of genomic and proteomic data in the most efficient manner possible. To obtain this goal, the general philosophy of the BIC is that responsibility for data interpretation should reside with the individual investigators since they are the experts in the biological systems in which they are studying. Our responsibility as a core is to provide consistent preliminary data analysis, software tools, data management infrastructure, and training necessary for their success. This mission will be implemented through the following specific aims: (1) develop the infrastructure necessary to manage and store microarray and tandem affinity purification (TAP) data; (2) perform initial microarray data analysis for biomedical investigators and provide commercial and custom software tools for the visualization and analysis of microarray and TAP data; and (3) provide training and support to all biomedical investigators on the application and utilization of the software tools in relation to their specific analysis needs. For the large, complex datasets present in genomic and proteomic studies, the visual and intuitive capabilities of individual investigators must be coupled with computational analysis in order to recognize important patterns within the data. Establishing the BIC will insure a central repository will exist for all gene expression and TAP data and will enable efficient data mining to occur within and across projects.