Biostatistics Core

Phyllis Gimotty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， 尤其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 计划项目调查人员及其人员的专业知识，并与这些调查人员合作 使用统计模型和其他统计技术，以更好地了解病因和进展， 食道癌生物统计学核心教师和工作人员在癌症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拥有丰富的经验 本项目中提出的研究。他们将在以下领域提供专业知识，以支持其 研究目的：（1）研究基因相关因素和/或 相关蛋白相关因子，以及影响肿瘤生长的不同生物学因素， 模型;（2）统计设计和评估策略，以评估实验干预措施在 基因对相关生物学结果（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，使科学有效的声明有关 关键的科学假设。生物统计学核心成员将与项目研究人员合作， 解释和综合研究结果，合作编写手稿，并保持一个 链接所有分析数据库的数据库。这些合作将确保项目 继续有高质量的研究设计和统计分析计划，这将提供一个杰出的 从实验数据中建立统计模型和推论的基础。这个核心是动态的， 响应不断变化的P01需求，预测未来的P01方向，并整合新的统计 方法和模型， 相关性（参见说明）： 该核心对于确保项目内的实验设计和数据分析至关重要 是在一个严格的，综合的方式完成，并锻造新的方向的翻译组成部分， 计划项目。该核心在癌症研究方面拥有丰富的经验， 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.