Systems Biology and Bioinformatics Group

SBG的总体目标是提供几种已建立的生物信息学工具，并开发新的方法 对生成的AMP网络执行集成的多通道、多组织和多中心分析 数据。SBG的目标将是(1)与网络调查人员合作， 主要数据，(2)为数据分析提供可靠的生物信息学方法，(3)向 用于假设检验的网络调查人员，以及(4)通过协作发布数据以供公众使用 数据协调和管理核心(DCM)。SBG将与所有网络站点合作，以 满足他们对强大的生物信息学技术的需求，以识别生物标记物和途径 了解疾病机制并预测新的药物靶点。更重要的是，SBG将携带 通过整合通过网络获得的数据进行多队列、多组织的综合分析 公开可用的人类侧写数据的数量。此外，SBG将与DCM密切合作，以 将分析结果发布到Internet上。使用Galaxy和Stanford Data Miner，SBG将建立一个 与统计管理委员会和统计研究小组密切协作的综合分析管道 (SRG)，实现对来自人类、体外和中国的多种类型基因组规模数据的最先进分析 活体模型。这将使参与的网络站点能够最大限度地利用基因组、免疫力 监测、临床、表型和其他类型的数据，以确定 并指导对这些假定的依赖关系进行进一步的生物学验证。

The overall goal of the SBG is to provide several established bioinformatics tools, and develop new methods to perform integrated multi-modality, multi-tissue, and multi-center analysis of the AMP Network generated data. The goals of the SBG will be (1) to collaborate with the Network investigators that are generating primary data, (2) to provide robust bioinformatics methods for analysis of the data, (3) to serve data to the Network investigators for hypothesis testing, and (4) to publish the data for public availability in collaboration with the Data Coordination and Management Core (DCM). The SBG will work with all Network sites to address their need for robust bioinformatics techniques to identify biomarkers and pathways for understanding disease mechanisms and predicting novel drug targets. More importantly, the SBG will carry out integrated multi-cohort, multi-tissue analysis by integrating data obtained through the Network with large amounts of publicly available human profiling data. Furthermore, the SBG will work closely with the DCM to publish analysis results to the Internet. Using Galaxy and Stanford Data Miner, the SBG will establish a pipeline for integrated analysis, in close collaboration with the DCM and the Statistical Research Group (SRG), to enable state-of-the-art analysis of multiple types of genome-scale data from human, in vitro and in vivo models. This will enable participating Network sites to maximally utilize the genomic, immune monitoring, clinical, phenotypic, and other types of data to determine functional dependencies among the measured elements and to direct further biological validation of these putative dependencies.