Core C - Biostatistics & Bioinformatics Core

项目摘要 纽约大学黑色素瘤孢子的生物统计学和生物信息学核心（核心C）将提供统计和 为所有SPORE研究项目和核心提供生物信息学合作和咨询。协商是 从研究设计和规划阶段到实施、数据管理、统计和 生物信息学分析和结果解释。核心C将为所有拟议实验室提供支持 研究和转化研究，包括基于现有和新的样本的生物标志物开发 临床试验，以支持总体使命和中央科学战略的纽约大学黑色素瘤孢子。 此外，还提出了从所有项目中系统地选择样本和协调 核心C中的信息学支持将允许跨项目结果的整体整合， 预测治疗结果和毒性的综合模型。Core C借鉴并集成了广泛的 纽约大学朗格尼医学中心（NYULMC）和纽约大学的知识、资源和专业知识基金 Perlmutter癌症中心（PCC）为纽约大学黑色素瘤孢子服务。联合主任邵永昭博士是 PCC生物统计共享资源（BSR）副主任，Itai柳井博士是研究所所长 分别为计算医学，并将提供综合的生物统计和生物信息学支持 并确保最大限度地利用所有机构资源和设施。这将授权提供 统计设计各方面的专业知识;功效/样本量计算;系统样本选择 有效的数据整合和分析战略;以及整合来自多个来源的数据，包括 实验室数据、临床数据和来自不同测序平台的数据。核心C将开发创新 统计和生物信息学方法，包括可扩展的计算算法，用于识别和评估 生物标志物的翻译研究，并将使这些新开发的算法公开提供给 更大的癌症研究社区特别是，核心C的生物标志物的鉴定，可以优化 晚期黑色素瘤患者的个性化管理将使得能够开发综合的， 治疗反应和毒性的多变量预测模型。这项工作，基于生物标志物发现， 在整个孢子项目，将有助于个性化的黑色素瘤管理和放大翻译 纽约大学黑色素瘤孢子的影响。

PROJECT SUMMARY The Biostatistics and Bioinformatics Core (Core C) of the NYU Melanoma SPORE will provide statistical and bioinformatics collaboration and consultation to all SPORE Research Projects and Cores. Consultation is available from the study design and planning stages through implementation, data management, statistical and bioinformatics analysis, and interpretation of results. Core C will provide support for all proposed laboratory studies and translational studies, including biomarker development based on samples from existing and new clinical trials to support the overarching mission and central scientific strategy of the NYU Melanoma SPORE. Furthermore, strategies for the systematic selection of samples from all the projects and the coordination of informatics support in Core C will permit the overall integration of results across projects to develop comprehensive models to predict treatment outcomes and toxicity. Core C draws on and integrates an extensive fund of knowledge, resources, and expertise across the NYU Langone Medical Center (NYULMC) and NYU Perlmutter Cancer Center (PCC) to serve the NYU Melanoma SPORE. Co-Director Dr. Yongzhao Shao is Deputy Director of the PCC Biostatistics Shared Resource (BSR) and Dr. Itai Yanai is the Director of the Institute for Computational Medicine, respectively, and will provide integrated biostatistical and bioinformatics support and ensure maximum utilization of all institutional resources and facilities. This will empower the provision of expertise in all aspects of statistical design; power/sample size calculations; systematic sample selection strategies for efficient data integration and analyses; and integration of data from multiple sources including laboratory data, clinical data, and data from diverse sequencing platforms. Core C will develop innovative statistical and bioinformatics methods, including scalable computation algorithms, for identifying and evaluating biomarkers in translational studies, and will make these newly developed algorithms publicly available to the larger cancer research community. In particular, Core C’s identification of biomarkers that may optimize the personalized management of advanced melanoma patients will enable the development of integrated, multivariable predictive models for treatment response and toxicity. This work, based on biomarkers discovered across SPORE Projects, will contribute to personalized melanoma management and amplify the translational impact of the NYU Melanoma SPORE.