CORE--BIOINFORMATICS AND ENVIRONMENTAL BIOSTATISTICS

描述(申请人提供)：生物信息学和生物信息学的两个主要目标 生物统计学核心(BSIC)：1)领导统计/信息学推理和方法在中心研究中的应用，包括实验和观察性研究的设计和分析或结果数据；2)开发和应用创新的统计方法来处理中心研究数据，从而改进中心研究人员得出的科学推论。合作-BSIC的生物统计和生物信息学专家将积极参与中心成员的具体研究计划。例如，Zeger博士和Dominici博士目前在NMMAPS项目上与Samet博士合作，Irizarry博士与Tankersley博士在毒理学研究上合作。新的合作将在需要时通过教员之间的非正式讨论或通过向主任提出正式请求而出现。BSIC的教职员工是设计观察性和实验性研究的专家。他们与同事合作：精确定义假设，使其具有最大限度的可验证性；选择研究设计；尽可能精确地定义暴露和健康结果衡量标准，规划数据管理和分析方法。在现有方法不足的地方，他们还将开发新的方法来填补空白。

Description (provided by applicant): There are two main objectives of the Bioinformatics and Biostatistics Core (BSIC): 1) provide leadership on the application of statistical/informatics reasoning and methods in Center research, including the design of experimental and observational studies and analysis or the resulting data; 2) develop and apply innovative statistical methods to Center research data and to thereby improve scientific inferences drawn by Center investigators. Collaboration -the biostatistics and bioinformatics experts in the BSIC will actively participate with members of the Center on specific research programs. For example, Drs. Zeger and Dominici currently collaborate with Drs. Samet on the NMMAPS project and Dr. Irizarry collaborates with Dr. Tankersley on a toxicology study. New collaborations will arise as they are needed through informal discussions among faculty or by a formal request to the director. BSIC faculty are experts in the design of both observational and experimental studies. They work with their colleague to: precisely define the hypotheses so that they are maximally testable; choose the study design; define the exposure and health outcome measures as precisely as possible, plan data management and analytic methods. Where existing methods are inadequate, they will also develop novel methods to fill the void.