Core C- Data Analysis Core

核心C-数据分析核心

• 批准号: 10705756
• 负责人: Veerabhadran Baladandayuthapani
• 金额: $ 17.46万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-16 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10705756
• 关键词: Archives; Area; Bioinformatics; Biological Assay; Biometry; Cancer Biology; Cancer cell line; Case Report Form; Clinical Data; Clinical Research; Clinical Trials; Clinical Trials Design; Clinical Trials Network; Cohort Studies; Collaborations; Collection; Communication; Complement; DNA Damage; Data; Data Analyses; Data Collection; Data Set; Data Sources; Databases; Dedications; Dependence; Development; Diagnosis; Encyclopedias; Ensure; Epidemiology; Experimental Designs; Generations; Genetic; Genomics; Human Resources; Information Dissemination; Infrastructure; Institution; Investigational Therapies; Knowledge; Li-Fraumeni Syndrome; Link; Location; Malignant Neoplasms; Manuscripts; Maps; Methodological Studies; Methodology; Michigan; Molecular; Nature; Patients; Policies; Population Database; Prospective cohort; Quality Control; Registries; Reproducibility; Research; Research Activity; Research Design; Research Personnel; Resources; Sampling; Source; Time; Universities; Utah; Work; adverse event monitoring; career development; computational platform; data access; data management; data mining; data quality; data standards; drug sensitivity; epidemiology study; experience; experimental study; genomic data; health data; improved; leiomyosarcoma; member; multidisciplinary; novel strategies; programs; public repository; radiomics; research study; response; sample collection; single-cell RNA sequencing; transcriptome sequencing; translational study; trial design

Core C – Data Analysis Core - Summary/Abstract: The objective of the Data Analysis Core (DAC) is to provide a comprehensive, multidisciplinary resource for the research associated with the SPORE. The needs of these projects require a wide breath of biostatistics and bioinformatics analytical knowledge as well as computational expertise. The DAC will provide biostatistical and bioinformatic collaboration in support of the discovery, translational, and clinical studies associated with the SPORE research activities. The comprehensive nature of this core assures each SPORE investigator access to expertise that includes collaborative development of study designs, collection and management of data, generation of analysis plans, support for clinical trials, analysis of data, interpretation of data, development of computational platforms for data mining, and dissemination of results (e.g., abstracts, presentations, manuscripts). Furthermore, the DAC will facilitate knowledge-sharing among the projects and cores by identifying and communicating best practices, standardizing data when possible, centralizing data for use across the projects, and conveying results to SPORE investigators in a timely fashion. Finally, the core is poised to develop new methodology when needed to support the SPORE research as well as to adapt to changes in research strategy in response to new or unexpected findings. In summary, to support all proposed SPORE projects, the Career Development and Developmental Research Programs, the other cores, and related SPORE research, the DAC will (1) provide biostatistics and bioinformatics collaboration for all SPORE research activities, (2) facilitate data collection, management, integration, and storage for SPORE research activities, and (3) develop and implement methodology that enhances the research across the SPORE projects. The members of DAC will work closely with team members of each of the projects. In addition, they will collaborate closely with bioinformatics personnel within the research teams of the project PIs to ensure alignment of the statistical aspects with the bioinformatics efforts and allow the integration of bioinformatics data across projects. The members of DAC will engage in regular communication with SPORE projects, other Cores, SPORE PIs.

核心C-数据分析核心-摘要/摘要： 数据分析核心(DAC)的目标是为以下方面提供全面的多学科资源 与孢子有关的研究。这些项目的需求需要广泛的生物统计学和 生物信息学分析知识以及计算专业知识。发改委将提供生物统计学和 生物信息学协作，支持与该基因相关的发现、翻译和临床研究 孢子研究活动。这个核心的综合性确保了每个孢子调查者都可以访问 专业知识，包括研究设计的协作开发、数据的收集和管理； 生成分析计划、支持临床试验、分析数据、解释数据、开发 用于数据挖掘和结果传播的计算平台(例如，摘要，演示文稿， 手稿)。此外，发援会将通过以下方式促进项目和核心之间的知识共享： 以及传达最佳做法、尽可能标准化数据、集中数据以供跨 项目，并将结果及时传达给孢子调查人员。最后，核心已经准备好发展。 支持孢子研究以及适应研究变化所需的新方法 应对新的或意想不到的发现的策略。总括而言，为支持所有拟议的孢子项目， 职业发展和发展研究计划，其他核心，以及相关的孢子研究， DAC将(1)为所有孢子研究活动提供生物统计和生物信息学合作，(2) 促进孢子研究活动的数据收集、管理、集成和存储，以及(3)开发 并实施方法论，加强对孢子项目的研究。 发援会成员将与每个项目的团队成员密切合作。此外，他们还将 与PIS项目研究团队内的生物信息学人员密切合作，确保一致性 统计方面与生物信息学工作的关系，并允许将生物信息学数据 项目。DAC成员将与孢子项目、其他核心、孢子 PIS.