Next generation high throughput lipidomics using adaptive modelling

使用自适应建模的下一代高通量脂质组学

• 批准号: DP230101795
• 负责人: Dr Kevin Huynh
• 金额: $ 40.78万
• 依托单位: La Trobe University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP230101795
• 关键词: Next; generation; throughput; lipidomics; using

This project aims to develop a unique high-throughput method to capture the lipidomic profile of human plasma suitable for large human population screening. Lipids are fundamental to every biological system, but our understanding of their regulation in humans have been largely superficial. By incorporating a new lipidomics approach, with genomic data, this project aims to expand our understanding of human biology by identifying regulators of lipid metabolism. The large diversity in humans necessitate sufficient sample sizes to identify true genetic regulators, but to date techniques capturing phenotypic data (lipids) have been largely limited. It is anticipated that this study will identify new regulators of lipid metabolism in humans.

该项目旨在开发一种独特的高通量方法来捕获适合大规模人群筛查的人血浆脂质组学特征。脂质是每个生物系统的基础，但我们对它们在人类中的调节的理解在很大程度上是肤浅的。通过将新的脂质组学方法与基因组数据相结合，该项目旨在通过确定脂质代谢的调节因子来扩大我们对人类生物学的理解。 人类的巨大多样性需要足够的样本量来识别真正的遗传调节因子，但迄今为止，捕获表型数据（脂质）的技术在很大程度上受到限制。预计这项研究将确定人类脂质代谢的新调节剂。