The ABC of reverse engineering biological signalling systems.
The ABC of reverse engineering biological signalling systems.
复制标题
逆向工程生物信号系统的基础知识。
作者：
M. Secrier;Tina Toni;M. Stumpf
如果我们知道模型的结构和控制其动力学的参数，对生物系统进行建模将是直截了当的。然而，对于绝大多数生物过程，这些参数值是未知的，并且通常不可能直接测量。这意味着我们必须从观测数据中估计或推断这些参数。在这里，我们认为，它也是重要的，以欣赏这些估计固有的不确定性。我们讨论了一种统计方法-近似贝叶斯计算（ABC）-这使我们能够近似参数的后验分布，并显示这可以如何增加我们对系统动态的理解。我们说明了这种方法的应用，以及如何得到的后验分布可以分析的情况下，有丝分裂原活化蛋白激酶磷酸化级联反应。我们的分析还强调了使用参数的分布，而不是参数值的点估计时，考虑系统生物学中的草率模型的概念的额外好处。
Modelling biological systems would be straightforward if we knew the structure of the model and the parameters governing their dynamics. For the overwhelming majority of biological processes, however, such parameter values are unknown and often impossible to measure directly. This means that we have to estimate or infer these parameters from observed data. Here we argue that it is also important to appreciate the uncertainty inherent in these estimates. We discuss a statistical approach--approximate Bayesian computation (ABC)--which allows us to approximate the posterior distribution over parameters and show how this can add insights into our understanding of the system dynamics. We illustrate the application of this approach and how the resulting posterior distribution can be analyzed in the context of the mitogen-activated protein kinase phosphorylation cascade. Our analysis also highlights the added benefit of using the distribution of parameters rather than point estimates of parameter values when considering the notion of sloppy models in systems biology.
草率模型普遍性类和范德蒙德矩阵。
影响因子：
8.6
作者：
Waterfall,JoshuaJ;Casey,FergalP;Gutenkunst,RyanN;Brown,KevinS;Myers,ChristopherR;Brouwer,PietW;Elser,Veit;Sethna,JamesP
通讯作者：
Sethna,JamesP