Data Management and Analysis Core

数据管理与分析核心

基本信息

批准号：
10354694
负责人：
Shesh N. Rai
金额：
$ 17.17万
依托单位：
UNIVERSITY OF LOUISVILLE
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10354694
关键词：
Anacondas Animals Artificial Intelligence Basic Science Bioinformatics Biological Assay Biometry Cardiometabolic Disease Characteristics Clinical Investigator Clinical Research Clinical Trials Code Collaborations Consultations Data Data Analyses Data Collection Data Files Data Set Data Storage and Retrieval Databases Development Dimensions Disease Educational workshop Ensure Environment Environmental Exposure Evaluation Experimental Designs Exposure to FAIR principles Faculty Fostering Funding Future Gases Geography Hazardous Chemicals Health Human Human Resources Individual Institution Linux Machine Learning Manuscripts Maps Mass Spectrum Analysis Measurement Methods Modeling Molecular Operating System Output Participant Population Analysis Postdoctoral Fellow Preparation Prevention Privacy Procedures Process Protocols documentation Pythons Quality Control Research Research Design Research Personnel Resources Risk Risk Assessment Sampling Scientist Secure Series Services Site Source Spatial Distribution Specimen Statistical Data Interpretation Statistical Methods Study Subject Superfund Testing Toxic effect Training Translational Research Universities Validation Variant Work archive data archived data base cardiometabolism central database cohesion computing resources data curation data dictionary data exchange data harmonization data hub data interoperability data management data quality data sharing data streams data structure design detection limit disorder risk education resources efficacy testing epidemiology study experience experimental analysis graduate student improved innovation land use large datasets lipidomics meetings metabolomics novel novel strategies operation platform-independent portability preclinical study quality assurance repository statistical service tool transcriptomics usability volatile organic compound

项目摘要

PROJECT SUMMARY The primary objective of the Sample and Data Management Core (DMAC) is to provide statistical support and data management and storage capabilities to all components of the University of Louisville Superfund Research Center (ULSRC). The functions of the Core are matched to the needs of each project and cover a full range of services from collaboration and routine service to protocol preparation to procedural review and oversight. The Core will provide two main services: it will establish a repository for the long-term storage and archiving of data; and it will assist Center investigators in the statistical analysis of their results. The core will assure the authenticity and quality of these specimens and it will prepare these samples for long-term storage, or dispense samples as needed. The Core will also provide scientifically valid and rigorous statistical analysis of data and support the development of innovative methods to enhance the basic and translational research efforts of Center investigators. It will provide state-of-the-art biostatistics and bioinformatics expertise and analytical support. Core biostatisticians will also develop new statistical methods, such as quantitative risk assessment models, multipollutant exposure analysis, and land-use regression models, for estimating cardiometabolic disease risk in exposed populations and for the analysis and evaluation of exposures and health effects. In collaboration with other projects and cores, DMAC, statisticians will harmonize the data by defining standards (e.g., creating searchable data dictionaries and defining variables relevant for each project. In the next funding cycle, we will continue to use these procedures. The core will serve as a unique educational resource for training graduate students, post-doctoral fellows, residents and junior faculty and in collaboration with the Training and Administration Cores. This Core will allow Center investigators easy access to high quality, centralized data management and statistical services, and thereby will strengthen the organizational cohesion of the Center. This comprehensive and integrated service permits one or more biostatisticians to be involved from the initial planning stage of a project (when statistical consultation is most beneficial) throughout its implementation, analysis and completion. The Core will provide a stable and collegial environment that fosters long-term working relationships between biostatisticians and investigators, and continues to promote sophisticated approaches to experimental design and analysis. The biostatisticians of this Core are knowledgeable about clinical research and have broad expertise in statistical applications for epidemiological investigations, clinical trials, pre-clinical studies, and prevention and control research. Their interdisciplinary interactions with basic scientists and clinical investigators will add a new dimension to the interpretation of experimental results, one that is only possible when collaborators share a mutual appreciation of problems and issues.

项目概要样本和数据管理核心 (DMAC) 的主要目标是提供统计支持和路易斯维尔大学超级基金研究所有组件的数据管理和存储功能中心（ULSRC）。核心的功能与每个项目的需求相匹配，涵盖全方位从协作和日常服务到方案准备再到程序审查和监督。这 Core将提供两项主要服务：建立一个存储库，用于数据的长期存储和归档；它将协助中心研究人员对其结果进行统计分析。核心将保证真实性和这些样本的质量，它将准备这些样本以供长期储存，或按以下方式分配样本需要。核心还将提供科学有效和严格的数据统计分析，并支持开发创新方法以加强中心的基础研究和转化研究工作调查人员。它将提供最先进的生物统计学和生物信息学专业知识和分析支持。核生物统计学家还将开发新的统计方法，例如定量风险评估模型，多污染物暴露分析和土地利用回归模型，用于估计心脏代谢疾病风险暴露人群以及分析和评估暴露和健康影响。与合作其他项目和核心、DMAC、统计学家将通过定义标准（例如，创建可搜索的数据字典并定义与每个项目相关的变量。在下一个融资周期，我们将继续使用这些程序。该核心将作为培养毕业生的独特教育资源学生、博士后研究员、住院医生和初级教师，并与培训和管理核心。该核心将使中心调查人员能够轻松访问高质量的集中数据管理和统计服务，从而加强中心的组织凝聚力。这全面综合的服务允许一名或多名生物统计学家从最初的规划开始就参与其中项目的整个实施、分析和实施阶段（此时统计咨询最有利）完成。核心将提供一个稳定的合作环境，促进长期的工作关系生物统计学家和研究人员之间的合作，并继续推广复杂的实验方法设计和分析。该核心的生物统计学家熟悉临床研究并拥有广泛的知识流行病学调查、临床试验、临床前研究的统计应用专业知识防治研究。他们与基础科学家和临床研究人员的跨学科互动将为实验结果的解释增加一个新的维度，只有合作者才能实现这一点对问题和问题有共同的认识。