Friedman Nir, Cai Long, Xie X Sunney
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.
Phys Rev Lett. 2006 Oct 20;97(16):168302. doi: 10.1103/PhysRevLett.97.168302. Epub 2006 Oct 19.
We present an analytical framework describing the steady-state distribution of protein concentration in live cells, considering that protein production occurs in random bursts with an exponentially distributed number of molecules. We extend this framework for cases of transcription autoregulation and noise propagation in a simple genetic network. This model allows for the extraction of kinetic parameters of gene expression from steady-state distributions of protein concentration in a cell population, which are available from single cell data obtained by flow cytometry or fluorescence microscopy.
我们提出了一个分析框架，用于描述活细胞中蛋白质浓度的稳态分布，其中考虑到蛋白质产生是以分子数量呈指数分布的随机爆发形式发生的。我们将这个框架扩展到简单遗传网络中的转录自调控和噪声传播的情况。该模型能够从细胞群体中蛋白质浓度的稳态分布提取基因表达的动力学参数，这些参数可从通过流式细胞术或荧光显微镜获得的单细胞数据中获取。
