Regression models for genetic and genomic data

遗传和基因组数据的回归模型

• 批准号: 9242-2009
• 负责人: Bull, Shelley
• 金额: $ 2.77万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=497417
• 关键词: Regression; models; genetic; genomic; data

The general objective of the research program is to develop new statistical tools to address current analytic problems in basic research in human biology and complex disease, at the levels of the individual, the family, and the population. I propose to develop statistical models and methods of data analysis that integrate the multiple sources of data and the inherent complex data structures in molecular biologic studies of the genetic and environmental factors that impinge on disease processes. New technologies for high-dimensional molecular measurement present new opportunities to refine analytic approaches to gene discovery and characterization and to gain insight into the underlying biology using statistical models.

该研究计划的总体目标是开发新的统计工具，以解决当前在人类生物学和复杂疾病的基础研究分析问题，在个人，家庭和人口的水平。我建议开发统计模型和数据分析方法，整合多种来源的数据和固有的复杂的数据结构，在分子生物学研究的遗传和环境因素，影响疾病的过程。高维分子测量的新技术为完善基因发现和表征的分析方法以及使用统计模型深入了解基础生物学提供了新的机会。