Bioinformatics and Data Management Core

生物信息学和数据管理核心

• 批准号: 9205191
• 负责人: Daniel L Gillen
• 金额: $ 27.81万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9205191
• 关键词: Affect; Alzheimer' s Disease; Alzheimer' s disease model; Animal Model; Animals; Area; Bioinformatics; Biological Markers; Cells; Clinical Data; Data; Data Analyses; Data Collection; Data Sources; Databases; Development; Disease Progression; Disease model; Encyclopedia of DNA Elements; Faculty; Gene Expression; Genetic; Genetic Transcription; Genotype-Tissue Expression Project; Heterogeneity; Housing; Human; Medicine; Methodology; Methods; Modeling; Molecular Profiling; Neurology; Pathological Staging; Phenotype; Preclinical Testing; Proteomics; Protocols documentation; Recording of previous events; Research; Research Methodology; Resources; Source; Standardization; Statistical Models; Subgroup; Testing; Time; Translating; Validation; acronyms; data acquisition; data management; design; flexibility; innovation; member; metabolomics; model development; mouse model; neuroimaging; neuropathology; next generation; novel; pre-clinical; predictive modeling; risk variant; statistics; transcriptome sequencing; web site

SUMMARY The primary objectives of the Bioinformatics and Data Management Core (BDMC) are to: (1) develop and implement standardized data acquisition and data analysis protocols across the NexGen AD Models Center (NG-ADMC), (2) acquire and integrate external data to inform AD animal models generated by the NG-ADMC, and (3) create and maintain a publicly available database to house research data generated by the NG-ADMC. The BDMC is led by faculty members with a long-standing history of directing bioinformatics, statistics, and data cores, with particular expertise in AD and neurology. The BDMC will be instrumental in the development and application of statistical models and bioinformatics methodologies as applied to the analysis of animal model discoveries. These analyses will be used for validation purposes as well as in the refinement of existing models. Specifically, faculty within the BDMC will build flexible predictive models using multiple clinical data sources in order to identify and prioritize LOAD risk alleles, and to analyze gene expression profiles, proteomics, and metabolomics data for implementation in animal models. They will also develop and apply efficient sequential testing designs for testing identified mouse models, and use robust post-hoc subgroup identification methods for assessing potential subpopulation heterogeneity in the effect of globally non- efficacious candidate therapies. The end result will allow the BDMC to identify and validate translatable biomarkers that can ultimately assist in clinico-pathological staging of an AD-like disease progression in AD animal models.

摘要 生物信息学和数据管理核心(BDMC)的主要目标是：(1)开发和 在NexGen AD模型中心实施标准化的数据采集和数据分析协议 (2)获取并整合外部数据，以告知NG-ADMC生成的AD动物模型， 以及(3)创建和维护一个公开可用的数据库，以存储NG-ADMC产生的研究数据。 BDMC由具有长期指导生物信息学、统计学和 数据核心，具有AD和神经学方面的特殊专业知识。BDMC将在开发过程中发挥重要作用 以及统计模型和生物信息学方法在动物分析中的应用 模型发现。这些分析将用于验证目的以及改进现有的 模特们。具体地说，BDMC中的教员将使用多种临床数据建立灵活的预测模型 来源：为了识别和区分负荷风险等位基因的优先顺序，并分析基因表达谱， 蛋白质组学和代谢组学数据，以便在动物模型中实施。它们还将开发和应用 高效的顺序测试设计，用于测试已识别的小鼠模型，并使用健壮的后自组织子组 全球非生物多样性影响下潜在亚种群异质性的识别方法 有效的候选疗法。最终结果将允许BDMC识别和验证可翻译 最终有助于AD病样疾病进展的临床病理分期的生物标志物 动物模型。