Research Support Core: Environmental Statistics

但前提是。 环境统计和生物信息学核心将提供尖端的生物统计和 为所有项目提供生物信息学设计和分析支持。核心教员从系里抽调出来。的 生物统计学的环境统计程序，定量基因组学的HSPH程序 生物信息学核心，系。流行病学系和国防部。年的环境健康计划 环境流行病学。核心教员在协作和方法开发方面有很强的历史 在环境健康研究和遗传流行病学方面的应用。专门知识的具体领域 包括非参数平滑、贝叶斯方法、空间统计、纵向数据分析 环境风险评估、统计遗传学、生物信息学、全基因组关联研究 基因和环境。生物统计学的学生和博士后研究员也将提供数据分析 根据需要提供支持。除了处理和监督所有项目的统计设计和分析外， 核心意愿： ？就数据管理提供建议，并确保所有项目采用适当的质量控制/质量 确保数据收集、录入、存储和检索； ？提供统计方法培训，指导博士生从事相关研究工作 项目； ？安排研讨会、研讨会和阅读小组，以确保所有计划教职员工和研究人员 掌握与生物信息学相关的最先进的统计方法、程序和技术； ？开展与任务有关的统计研究。

PROVIDED. The Environmental Statistics and Bioinformatics Core will provide cutting edge biostatistical and bioinformatics design and analysis support for all projects. Core faculty are drawn from the Dept. of Biostatistics's Environmental Statistics Program, the HSPH Program of Quantitative Genomics, the HSPH Bioinformatics Core, the Dept. of Epidemiology, and the Dept. of Environmental Health's Program in Environmental Epidemiology. Core faculty have a strong history of collaboration and methods development for applications in environmental health research and genetic epidemiology. Specific areas of expertise include nonparametric smoothing, Bayesian methods, spatial statistics, longitudinal data analysis, environmental risk assessment, statistical genetics, bioinformatics, genome-wide association studies, and genes and environment. Students and postdoctoral fellows in Biostatistics will also provide data analysis support as needed. In addition to handling and overseeing statistical design and analysis for all projects, the core will: ¿ Advise on data management and ensure that all projects adopt appropriate quality control/quality assurance for data collection, entry, storage and retrieval; ¿ Provide training in statistical methods and supervise doctoral students working on related research projects; ¿ Arrange for workshops, seminars and reading groups to ensure that all program faculty and researchers have access to state ofthe art statistical methods, programs and techniques related to bioinformatics; ¿ Conduct mission-related statistical research.