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

我们打算开发综合数学模型，利用尖端技术的力量，下一代测序（NGS），以解释细胞如何对不同的压力作出反应。在包括人类在内的多细胞生物体中，一个检查和平衡系统阻止受损细胞繁殖。这些系统的失败导致癌症，其中细胞增殖不受抑制。我们将如何研究细胞？决定？生与死我们将使用的技术使我们能够同时测量，非常精确，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它们的命运。由于基因活性对所有健康和疾病状态都很重要，我们将开发的技术将广泛适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，更准确地使用最新技术产生的复杂数据。最终，这些方法将极大地提高我们对疾病的理解，如遗传性疾病，复杂的疾病，如心脏病和癌症。

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.