Core C - Biostatistics & Bioinformatics Core

项目总结 纽约大学黑色素瘤孢子的生物统计和生物信息学核心(核心C)将提供统计和 所有孢子研究项目和核心的生物信息学合作和咨询。咨询是 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将为所有拟建的实验室提供支持 研究和翻译研究，包括基于现有和新样本的生物标记物开发 支持纽约大学黑色素瘤孢子总体使命和中心科学战略的临床试验。 此外，系统地从所有项目中选择样本的战略和协调 核心C中的信息学支持将允许开发跨项目的结果的整体集成 预测治疗结果和毒性的综合模型。核心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 佩尔穆特癌症中心(PCC)为纽约大学黑色素瘤孢子提供服务。副主任邵永照博士是 PCC生物统计共享资源(BSR)副主任伊泰·柳艾博士是研究所所长 分别用于计算医学，并将提供综合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 精通统计设计的方方面面；能力/样本量计算；系统样本选择 有效整合和分析数据的策略；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将发展创新 统计和生物信息学方法，包括可伸缩计算算法，用于识别和评估 生物标记物，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，Core C对生物标志物的识别可能会优化 晚期黑色素瘤患者的个性化管理将使综合、 治疗反应和毒性的多变量预测模型。这项工作基于发现的生物标记物 跨孢子项目，将有助于个性化黑色素瘤管理并放大翻译 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.