New statistical methods for identifying micro-ribonucleic acid (miRNA) regulatory networks

识别微核糖核酸 (miRNA) 调控网络的新统计方法

• 批准号: FT0991918
• 负责人: Prof Jean Yang
• 金额: $ 45.48万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2010
• 资助国家: 澳大利亚
• 起止时间: 2010-02-25 至 2016-03-17
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT0991918
• 关键词: New; statistical; methods; identifying; micro

Understanding gene regulatory networks is critical in the understanding of fundamental biological systems. These networks have important implications for the discovery of fundamental mechanisms relating to the diagnosis and management of many illnesses. This research will provide new statistical methods to identify regulatory micro-ribonucleic acid modules and to understand their relationship in gene regulatory networks through multiple covariance estimation and multivariate classification techniques. My results should enable researchers to better understand the regulation underlying biological systems, leading to improved human health, medical and biological research outcomes.

了解基因调控网络对于理解基本生物系统至关重要。这些网络对于发现与许多疾病的诊断和管理有关的基本机制具有重要意义。本研究将提供新的统计方法，以确定调控微核糖核酸模块，并通过多重协方差估计和多变量分类技术，了解它们在基因调控网络中的关系。我的研究结果应该使研究人员能够更好地了解生物系统的调节，从而改善人类健康，医学和生物学研究成果。