Biostatistics Core

在菲利斯·吉莫蒂博士领导下的生物统计学核心拥有丰富的生物统计学经验， 特别是在癌症生物学和治疗方面。生物统计核心的目标是提供生物统计 向方案项目调查员及其人员提供专业知识，并与这些调查员合作 使用统计模型和其他统计技术来更好地了解该病的病因和进展 食道癌。生物统计学的核心教职员工在癌症研究和研究方面拥有丰富的经验 在拟议的统计方法及其在研究中的应用方面有丰富的经验 本计划项目中提出的研究。他们将在以下领域提供专业知识，以支持其 研究目的：(1)用统计学方法研究基因相关因素之间和(或)基因相关因素之间的关系 相关蛋白相关因子以及不同生物中影响肿瘤生长的因素 模型；(2)评估#年实验干预措施影响的统计设计和评价战略 与相关生物结果相关的基因(细胞增殖和凋亡、肿瘤生长和发育、 治疗反应)；和(3)统计决策工具，以作出科学有效的相关陈述 关键的科学假说。生物统计核心成员将与项目调查人员合作 解释和综合研究结果，合作准备手稿，并保持 链接所有分析数据库的数据库库。这些合作将确保项目 继续拥有高质量的研究设计和统计分析计划，这将提供出色的 根据实验数据建立了统计模型和推论。此核心在中是动态的 响应不断发展的P01需求，预测未来P01方向，整合新的统计数据 方法和模型， 相关性(请参阅说明)： 该核心对于确保项目内的实验设计和数据分析至关重要 以严格、集成的方式完成，并在翻译组件中形成新的方向 计划项目。这一核心在癌症研究方面拥有丰富的经验，该项目使用 项目。

The Biostatistics Core under the Directorship of Dr. Phyllis Gimotty has vast biostatistical experience, especially in cancer biology and therapy. The goals of the Biostatistics Core are to provide biostatistical expertise to Program Project investigators and their personnel, and in collaboration with these investigators to use statistical models and other statistical techniques to better understand the etiology and progression of esophageal cancer. The Biostatistics Core faculty and staff have vast experience in cancer research and extensive experience with the proposed statistical methodologies and their application to the research studies proposed in this Program Project. They will provide expertise in the following areas to support its research objectives: (1) statistical methods to study associations among gene-related factors and/or among associated protein-related factors, as well as factors that influence tumor growth in different biological models; (2) statistical design and evaluation strategies to assess the impact of experimental interventions in genes on relevant biological outcomes (cell proliferation and apoptosis, tumor growth and development, therapeutic response); and (3) statistical decision making tools to make scientifically valid statements related to key scientific hypotheses. The Biostatistics Core members will collaborate with project investigators to interpret and synthesize study findings, collaborate on the preparation of manuscripts and maintain a database library linking all of the analytic databases. These collaborations will ensure that the projects continue to have high quality study designs and statistical analysis plans, which will provide an outstanding foundation for statistical models and inferences made from the experimental data. This Core is dynamic in responding to evolving P01 needs, anticipating future P01 directions, and integrating new statistical methodologies and models, RELEVANCE (Seeinstructions): This Core is of vital importance to ensure that the experimental design and data analyses within the Projects are done in a rigorous, integrated fashion, and to forge new directions in the translational components of the Program Project. This Core has a wealth of experience in cancer research that is used by the Program Project.