Modelling transcriptional dynamics in human T-Cells using next generation sequencing data

使用下一代测序数据模拟人类 T 细胞的转录动力学

• 批准号: G0902107/1
• 负责人: Martino Barenco
• 金额: $ 53.27万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=G0902107%2F1
• 关键词: Modelling; transcriptional; dynamics; human; Cells

We intend to develop integrated mathematical models which harness the power of cutting edgetechnology, next generation sequencing (NGS), to explain how cells respond to different stresses. Inmulticellular organisms, including humans, a system of checks and balance prevents damaged cellsfrom multiplying. Failure of these systems results in cancer, where cells proliferate unchecked. Wewill study how cells ?decide? between life and death. The technology we will use allows us tosimultaneously measure, with great accuracy, the levels of all gene products in the genome. We willanalyse these measurements by developing mathematical models run on computers, which will leadto a better understanding of how gene activity in stressed cells determines their fate. Because geneactivity is important for all healthy and diseased states, the techniques we will develop will be widelyapplicable in other biomedical contexts. The approaches allow a much more efficient use ofexperimental materials and a more accurate use of the complex data generated by the latesttechnology. Ultimately these methods will greatly improve our understanding of diseases like geneticdisorders, complex diseases like heart disease and cancer.

我们打算开发综合数学模型，利用尖端技术、下一代测序（NGS）的力量来解释细胞如何响应不同的压力。在包括人类在内的多细胞生物体中，制衡系统可以防止受损细胞繁殖。这些系统的故障会导致细胞不受控制地增殖而导致癌症。我们将研究细胞如何“决定”？生与死之间。我们将使用的技术使我们能够非常准确地同时测量基因组中所有基因产物的水平。我们将通过开发在计算机上运行的数学模型来分析这些测量结果，这将有助于更好地理解应激细胞中的基因活动如何决定其命运。由于基因活性对于所有健康和疾病状态都很重要，因此我们将开发的技术将广泛应用于其他生物医学领域。这些方法可以更有效地使用实验材料，并更准确地使用最新技术生成的复杂数据。最终，这些方法将极大地提高我们对遗传性疾病、心脏病和癌症等复杂疾病的理解。