Core B: Biostatistics Core

生物统计和信息学核心的首要目标是提供统计、信息和 为方案项目提供计算支持，以进行先进和大规模的统计分析 识别和表征危险因素在预测和筛查肺癌中的准确性。核心教员 和其他研究人员在问题和方法论的推动下从事与任务相关的研究 这些项目带来的挑战。这个核心的成员拥有广泛的专业知识和兴趣 将他们的活动统一在项目中。通过形成生物统计学和信息学的核心， 项目，我们预计对项目研究的支持将比预期的更强劲和更深入 如果生物统计学家嵌套在每个项目中，就能实现这一目标。核心允许我们集中资源(例如 统计遗传学、统计学和机器学习方面的专业知识)，并利用更广泛的 多个参与机构提供的资源，如哈佛大学生物统计系 陈公共卫生学院和达特茅斯大学生物医学数据科学系。这个 核心成员在开发和应用新的统计和统计方法方面拥有丰富的经验 用于癌症风险预测和风险评估的遗传易感性研究的机器学习方法。 多年来，他们一直在合作研究与肺癌发展有关的问题。该核心提供了 协调和规划整个计划项目的研究以及开发和应用的环境 符合本计划项目需要的最先进的统计和机器学习方法。至 为了支持方案项目，我们提出了以下目标：(1)确保所有项目都植根于 健全的生物统计学和信息学原理，并使用最先进的方法进行设计和分析； 提供与统计遗传学、生物信息学和机器相关的设计和分析方面的专家建议 所有项目的学习和统计学习；(3)开展与特派团有关的统计方法研究 开发新的统计方法，以满足方案项目的量化需求；(4) 通过说明性文章、案例研究和 网络共享软件；(5)通过与 指导委员会和项目调查员。核心成员将协调他们的工作活动和 通过每月召开电话会议和定期交换电子邮件，有效地支持计划项目。

The overarching goal of the Biostatistics and Informatics Core is to provide statistical, informatic and computational support for the Program Project to conduct advanced and large-scale statistical analyses to identify and characterize the accuracy of risk factors in predicting and screening lung cancer. The Core faculty and other researchers engage in mission-related research motivated by questions and methodological challenges that arise from these projects. The members of this Core have extensive expertise and interests that unite their activities among Projects. By forming a Biostatistics and Informatics Core that functions across projects, we anticipate a more robust and profound level of support for Program research than could be achieved if biostatisticians were nested within each project. The Core allows us to pool resources (e.g. expertise in statistical genetics, statistical and machine learning) across projects and also draw on the broader resources available in multiple participating institutes, such as the Department of Biostatistics at Harvard TH Chan School of Public Health and the Department of Biomedical Data Science at Dartmouth University. The members of the Core have extensive experience in the development and application of new statistical and machine learning methods for the study of genetic susceptibility to cancer risk prediction, and risk assessment. They have worked together over years on studies relating to lung cancer development. The Core provides an environment for coordinating and planning of research across the program projects and to develop and apply state-of-the-art statistical and machine learning methods that meet the needs of this Program Project. To support the Program projects, we propose the following aims: (1) To ensure that all Projects are grounded in sound biostatistical and informatic principles and use state-of-the-art methods for design and analysis; (2) To provide expert advice related to design and analysis in statistical genetics, bioinformatics, and machine learning and statistical learning for all Projects; (3) To conduct mission-related statistical methods research by developing novel statistical methods to address the quantitative needs of the Program Project; (4) To disseminate the proposed statistical methodological developments via expository articles, case studies, and web-shared software; (5) To provide education and training for researchers and students by working with the Steering Committee and the Program investigators. The Core members will coordinate their work activities and effectively support the Program Project by having monthly conference calls and regular email exchanges.