Biostatistics for Spatial and High-Dimensional Data

空间和高维数据的生物统计学

• 批准号: CRC-2018-00246
• 负责人: Nathoo, Farouk
• 金额: $ 3.64万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=660693
• 关键词: Biostatistics; Spatial; Dimensional; Data

Recent technological advances in molecular biology and in neuroimaging have given rise to numerous large-scale studies involving combined imaging and genetic data. These datasets lead to very challenging problems such as the problem of conducting inference on the association between two blocks of data representing brain images and genetic data, the size and complexity of the data, sample size issues, nonlinear relationships between variables, the required computation, and checking model assumptions. The research proposed here will address these challenges.

最近在分子生物学和神经影像学方面的技术进步已经引起了许多涉及结合成像和遗传数据的大规模研究。这些数据集导致非常具有挑战性的问题，例如对表示大脑图像和遗传数据的两个数据块之间的关联进行推断的问题，数据的大小和复杂性，样本大小问题，变量之间的非线性关系，所需的计算和检查模型假设。本文提出的研究将解决这些挑战。