Statistical methods for analysing multi-source microarray data and building gene regulatory networks

分析多源微阵列数据和构建基因调控网络的统计方法

• 批准号: DP1095320
• 负责人: Dr Vivek Jayaswal
• 金额: $ 17.48万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2010
• 资助国家: 澳大利亚
• 起止时间: 2010-01-28 至 2013-01-26
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP1095320
• 关键词: Statistical; methods; analysing; multi; source

I will devise a statistical learning technique that does not force a gene to be assigned to exactly one category. This technique reflects the biological reality that a gene can belong to two or more functional categories. Therefore, the new technique will improve a model's ability to identify regulatory genes in different types of cancer; these regulatory genes can be targeted by new anti-cancer drugs resulting in a more effective treatment. I will model gene regulatory networks using microarray data from multiple sources. These networks will be used to identify regulatory cliques - a group of genes that are vital for a cellular function. This will improve our understanding of debilitating conditions such as asthma.

我将设计一种统计学习技术，不会强制将基因分配到确切的一个类别。该技术反映了一个基因可以属于两个或多个功能类别的生物学现实。因此，新技术将提高模型识别不同类型癌症中调控基因的能力；这些调节基因可以成为新的抗癌药物的目标，从而获得更有效的治疗。我将使用来自多个来源的微阵列数据对基因调控网络进行建模。这些网络将用于识别调控团——一组对细胞功能至关重要的基因。这将增进我们对哮喘等使人衰弱的疾病的了解。