Biostatistics Shared Resource

生物统计共享资源

• 批准号: 7623559
• 负责人: PHILIP WILLIAM LAVORI
• 金额: $ 13.97万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7623559
• 关键词: Biometry; Biostatistics Shared Resource; Cancer Center; Clinical; Clinical Trials; Collaborations; Computer software; Consult; Data Analyses; Development; Elements; Experimental Designs; Faculty; Future; Goals; Human Resources; Informatics; Leadership; Methods; Monitor; Observational Study; Phase; Population Research; Randomized; Range; Research; Research Infrastructure; Research Personnel; Resource Sharing; Sample Size; Scientist; Services; Statistical Methods; Strategic Planning; System; Translational Research; anticancer research; data management; design; genetic association; improved; innovation; member; programs

The objective of the Biostatistics Shared Resource is to support Stanford Cancer Center investigators in all phases of their research. Services include routine biostatistics support in addition to innovative methods developed specifically to enhance the basic and translational research efforts of a discoveryoriented Cancer Center faculty. As a dedicated service with a clear means of access, the Biostatistics Shared Resource greatly benefits those researchers in need of statistical support in their studies. Since official inception of this Shared Resource in 2005, over 20 researchers have used biostatistics services, representing ten Research Programs. Significant contributions by staff in this Shared Resource include new methods in microarray data analysis and genetic association studies. Future plans include recruitment of a biostatistics faculty member and additional staff as well as the development of an integrated data management system for cancer research.

生物统计学共享资源的目标是支持斯坦福癌症中心的研究人员 他们研究的所有阶段。服务包括常规生物统计支持以及创新 专门为加强以发现为导向的基础和转化研究工作而开发的方法 癌症中心教师。作为一项具有明确访问方式的专门服务，生物统计 共享资源极大地有益于那些在研究中需要统计支持的研究人员。自从 该共享资源于 2005 年正式启动，已有 20 多名研究人员使用了生物统计服务， 代表十个研究项目。工作人员在此共享资源中的重大贡献包括 微阵列数据分析和遗传关联研究的新方法。未来的计划包括 招聘一名生物统计学教员和其他工作人员以及开发一个 用于癌症研究的综合数据管理系统。