Information theoretic approaches to optimise genome wide association studies with application to continuous and discrete traits

优化全基因组关联研究的信息论方法，应用于连续和离散性状

• 批准号: DP110102041
• 负责人: Prof John Hopper
• 金额: $ 24.4万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2011
• 资助国家: 澳大利亚
• 起止时间: 2011-04-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP110102041
• 关键词: Information; theoretic; approaches; optimise; genome

This project aims to develop new mathematical methods to find genetic associations from new genome-wide studies of colorectal cancer and breast cancer risk factors. If successful, this will result in improved use of expensive genetic data to better predict and understand diseases, conditions and other characteristics for humans, animals and plants.

该项目旨在开发新的数学方法，从结直肠癌和乳腺癌风险因素的新全基因组研究中发现遗传关联。如果成功，这将导致更好地使用昂贵的遗传数据，以更好地预测和了解人类，动物和植物的疾病，状况和其他特征。