Core C - Biostatistics & Bioinformatics Core

核心 C - 生物统计学

• 批准号: 10652339
• 负责人: Yongzhao Shao
• 金额: $ 26.43万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-19 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10652339
• 关键词: Adjuvant; Algorithms; American; Autoantibodies; Bioinformatics; Biological Markers; Biometry; Biostatistics Shared Resource; Cancer Center; Caring; Clinical; Clinical Data; Clinical Trials; Collaborations; Communities; Computational algorithm; Consultations; Data; Data Analyses; Data Collection; Development; Doctor of Philosophy; Ensure; Epigenetic Process; Funding; Genetic; Grant; Immunologic Markers; Immunotherapy; Informatics; Institution; Joints; Knowledge; Laboratories; Laboratory Study; Leadership; Malignant Neoplasms; Medical center; Medicine; Methods; MicroRNAs; Mission; Modeling; Outcome; Patient Care; Patients; Prediction of Response to Therapy; Primary Neoplasm; Publications; Reporting; Reproduction spores; Research; Research Design; Research Personnel; Research Project Grants; Resources; Sample Size; Sampling; Source; Specific qualifier value; Statistical Data Interpretation; Toxic effect; Translational Research; Treatment outcome; Treatment-related toxicity; Tumor Tissue; Work; XCL1 gene; anticancer research; biomarker development; biomarker identification; cancer therapy; career; data integration; data management; design; diverse data; empowerment; genomic data; high dimensionality; immune-related adverse events; innovation; melanoma; member; microbial; microbiome; multiple data sources; open source; patient subsets; personalized management; personalized medicine; predictive marker; predictive modeling; predictive signature; randomized, clinical trials; senior faculty; sequencing platform; transcriptome sequencing; translational impact; translational study; treatment response

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.

项目摘要 NYU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 与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 通过实施，数据管理，统计以及从研究设计和计划阶段获得 生物信息学分析和结果的解释。 C核心将为所有拟议的实验室提供支持 研究和翻译研究，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NYU黑色素瘤孢子的总体任务和中心科学策略。 此外，从所有项目中系统地选择样品的策略和协调 核心C中的信息支持将允许整个项目的结果整体整合以开发 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 NYU Langone医疗中心（NYULMC）和NYU的知识，资源和专业知识基金 Perlmutter癌症中心（PCC）为NYU黑色素瘤孢子服务。联合导演Yongzhao Shao博士是 PCC生物统计学共享资源（BSR）副主任和Itai Yanai博士是该研究所的主任 分别用于计算医学，并将提供综合的生物统计和生物信息学支持 并确保最大程度地利用所有机构资源和设施。这将授权 统计设计各个方面的专业知识；功率/样本量计算；系统样本选择 有效数据集成和分析的策略；以及来自多个来源的数据的集成 来自潜水员测序平台的实验室数据，临床数据和数据。核心C将发展创新 用于识别和评估的统计和生物信息学方法，包括可扩展计算算法 转化研究中的生物标志物，并将使这些新开发的算法公开可供选择 更大的癌症研究界。特别是，Core C对生物标志物的识别可能优化 高级黑色素瘤患者的个性化管理将使综合的发展， 用于治疗反应和毒性的多变量预测模型。这项工作，基于发现的生物标志物 在各个孢子项目中，将有助于个性化的黑色素瘤管理并扩大翻译 NYU黑色素瘤孢子的影响。