Pan Omics and Data Science Core

泛组学和数据科学核心

• 批准号: 10393186
• 负责人: Maureen Agnes Sartor
• 金额: $ 22.94万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-15 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10393186
• 关键词: Address; Applications Grants; Applied Research; Area; Basic Science; Bioinformatics; Biological; Biological Assay; Cells; Classification; Clinical; Collaborations; Communities; Data; Data Science; Data Science Core; Data Scientist; Databases; Development; Disease; Environmental Exposure; Environmental Health; Environmental Impact; Epigenetic Process; Event; Evolution; Faculty; Funding; Genetic; Genomics; Health; Human; Hybrids; Laboratories; Link; Measures; Metagenomics; Methodology; Methods; Michigan; Mission; Molecular; National Institute of Environmental Health Sciences; Pathway Analysis; Phenotype; Population; Precision Health; Preparation; Process; Proteomics; Protocols documentation; Public Health; Publications; Recommendation; Regulation; Research; Research Design; Research Personnel; Resources; Sampling; Scientist; Services; Students; Techniques; Technology; Training; Translational Research; Translations; Visualization; Writing; base; bioinformatics tool; biomarker signature; community engagement; cost; data management; data sharing; data visualization; design; epigenomics; experience; genome-wide; health science research; innovation; interest; member; metabolomics; multiple omics; new technology; novel; sample collection; statistical and machine learning; statistical learning; tool; transcriptomics

ABSTRACT (Pan Omics and Data Science Core) The use of multi-omics techniques, including single-cell omics, in environmental health sciences (EHS) research continues to grow rapidly, and the use of advanced machine learning and statistical learning techniques to make translational predictions with these data is becoming ever more essential. As such, staying on the cutting edge with these tasks can be overwhelming. The objective of the Pan Omics and Data Science (PODS) Core is to provide comprehensive and innovative support to investigators in the Michigan Center on Lifestage Environmental Exposures and Disease (M-LEEaD) for the study design, sample preparation, analysis, interpretation, and integration of a broad range of omics-based studies, and to educate them on available opportunities. The PODS Core streamlines the entire process of an omics study, allowing M- LEEaD investigators to dedicate more of their own resources to answering difficult environmental health science questions. Lifestage-specific exposures may have detrimental effects on human health via any of several mechanisms, including epigenetic, genetic, transcriptomic, proteomic, metagenomic, metabolomic, and adductomic. Thus, in the new funding period the PODS Core aims to broaden its reach both in terms of the omics technologies supported, and the statistical and data science methods used. We will achieve this through building a close-knit community of UM experts in these areas and interest/experience in EHS. The PODS Core objective will be accomplished through four specific aims. First, we will provide M-LEEaD investigators expertise in the study design and implementation of a broad range of molecular studies, including technology platform choice, sample collection and preparation, and engagement with key UM resources. Second, we will provide bioinformatics analysis and data science services for a broad range of omics approaches and integrative analyses. Third, the PODS Core will support the community through development of novel bioinformatics methods and tools and protocols for novel technologies staying apace with technological advancements. Finally, the PODS Core educates M-LEEaD Center faculty, staff, and students on omics assays and data science relevant to EHS research, and promotes partnerships between environmental scientists and data scientists. M-LEEaD investigators benefit from several free services and collaborative events offered by PODS, which enables and strengthens Fundamental Questions and also Application and Synthesis in the NIEHS Translational Research Framework.

摘要（泛组学和数据科学核心） 多组学技术，包括单细胞组学在环境健康科学中的应用 研究继续快速增长，先进的机器学习和统计学习的使用 利用这些数据进行平移预测的技术变得越来越重要。因此，在本发明中， 在这些任务中保持领先地位可能是压倒性的。泛组学和数据的目标 科学（PODS）核心是提供全面和创新的支持，在密歇根州的调查人员 生命阶段环境暴露和疾病中心（M-LEEaD）的研究设计，样本 准备，分析，解释和整合广泛的基于omics的研究，并教育 在可用的机会。PODS核心简化了组学研究的整个过程，允许M- LEEaD调查人员将投入更多的资源来解决困难的环境健康问题 科学问题。特定生命阶段的暴露可能通过以下任何方式对人类健康产生有害影响： 几种机制，包括表观遗传，遗传，转录组，蛋白质组，宏基因组，代谢组， 内收的因此，在新的供资期内，极轨道密度数据系统核心的目标是扩大其覆盖范围， 所支持的组学技术以及所使用的统计和数据科学方法。我们将通过以下方式实现这一目标： 在这些领域建立一个紧密联系的UM专家社区，并在EHS方面有兴趣/经验。PODS核心 将通过四个具体目标实现这一目标。首先，我们将提供M-LEEaD调查员 在研究设计和实施广泛的分子研究，包括技术， 平台选择、样品收集和制备以及与关键UM资源的合作。二是 为广泛的组学方法提供生物信息学分析和数据科学服务， 综合分析。第三，PODS核心将通过开发小说来支持社区 生物信息学方法和工具以及新技术的协议与技术保持同步 进步。最后，PODS核心教育M-LEEaD中心的教职员工和学生的组学 与EHS研究相关的分析和数据科学，并促进环境与健康之间的伙伴关系。 科学家和数据科学家。M-LEEaD研究人员受益于多项免费服务和协作 由PODS提供的活动，它使和加强基本问题，也应用和 NIEHS翻译研究框架中的综合。