Core C: Data Management and Analysis Core (DMAC)

摘要：数据管理和分析核心 数据管理和分析核心(DMAC)为UNC-SRP研究人员提供关键支持 管理和分析与主题有关的数据，“确定减少国际会计准则风险的新方法和 阐明IAS引起的代谢功能障碍的潜在机制，并着眼于疾病预防。这个 DMAC的目标是支持UNC-SRP的数据管理、集成和分析需求 研究人员将揭示IAS引起的代谢功能障碍/糖尿病的多因素决定因素。这个 DMAC的数据管理部分设在文艺复兴计算研究所(RENCI)。这个 通过联合国统计委员会--统计部，可以提供对刚果民主共和国的分析支持。每一个项目 将与DMAC密切合作，满足生物信息学、统计学和数据科学的需求。通过制作数据 可查找、可访问、可互操作和可重复使用(公平)，DMAC将最大限度地发挥影响并优化 识别高影响力洞察力的途径。北卡罗来纳大学-SRP的科学家在生物医学项目1-3中将产生广泛的 一套数据类型，包括与IAS相关的microRNA、转录因子和细菌在 肠道微生物群。环境项目4-5将生成与北卡罗来纳州(北卡罗来纳州)和 通过过滤进行IAS还原。DMAC将提供最先进的数据管理、管理和分析 这些不同类型的数据。具体地说，DMAC将：第一，开发UNC-SRP范围的全面数据 管理计划，包括高质量的数据生成和促进共享和互操作性的系统； 第二，通过实施最先进的生物信息学来促进UNC-SRP项目特定的研究活动 和生物统计学方法；第三，整合项目1-5的UNC-SRP数据，以了解IAS的风险 IAS相关代谢功能障碍/糖尿病的暴露和机制。共同努力，民主党将 向UNC-SRP提供数据管理、生物信息学、统计和数据方面的基本专业知识 集成，并为团队完成其使命做出重要贡献--为减少国际会计准则开发新的解决方案 以及通过机械性和转化性研究预防疾病。

ABSTRACT: DATA MANAGEMENT AND ANALYSIS CORE The Data Management and Analysis Core (DMAC) provides critical support for UNC-SRP researchers to manage and analyze data related to the theme, “Identifying novel methods to reduce iAs exposure and elucidating mechanisms underlying iAs-induced metabolic dysfunction with a vision for disease prevention.” The goal of the DMAC is to support the data management, integration, and analysis needs of the UNC-SRP researchers to reveal multi-factorial determinants of iAs-induced metabolic dysfunction/diabetes. The data management component of DMAC is housed in the Renaissance Computing Institute (RENCI). The analytical support of the DMAC is made possible through the UNC-Department of Statistics. Each of the projects in the SRP will work closely with DMAC for bioinformatic, statistical, and data science needs. By making data Findable, Accessible, Interoperable and Reusable (FAIR), the DMAC will maximize the impact and optimize the path to identifying high impact insights. The UNC-SRP scientists in Biomedical Projects 1-3 will generate a broad suite of data types that includes iAs-associated microRNAs, transcription factors, and bacterial presence in the gut microbiome. Environmental Projects 4-5 will generate data relevant to iAs levels in North Carolina (NC) and iAs reduction via filtration. The DMAC will provide state-of-the-art data management, stewardship, and analysis for these diverse types of data. Specifically, the DMAC will: first, develop UNC-SRP-wide comprehensive Data Management Plan to include high quality data generation and systems that foster sharing and interoperability; second, facilitate UNC-SRP Project-specific research activities by implementing state-of-the-art bioinformatic and biostatistical methods; and third, integrate UNC-SRP data across Projects 1-5 to understand risks of iAs exposure and mechanisms underlying iAs-associated metabolic dysfunction/diabetes. Together, the DMAC will provide the UNC-SRP with essential expertise in data management, bioinformatics, statistics, and data integration and critically contribute to the team fulfilling its mission- to develop new solutions for iAs reduction and disease prevention through mechanistic and translational research.