August Elias
Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland.
J Comput Biol. 2012 Aug;19(8):968-77. doi: 10.1089/cmb.2011.0134.
For realistic models in molecular biology, you need to consider the noise in the cellular and intracellular environments. In this article, we present a novel approach for testing the validity of nonlinear models representing a biological system affected by noise. Our approach is based on results by Kushner and Øksendal and uses computational techniques that rely on efficient solvers. By providing analytically upper bounds for the exit probability of solution trajectories of a system from a particular set in the phase space, we can compare measurement data with this prediction and try to invalidate models with certain parameter values or noise properties. Thus, our approach complements the usual methods that are based on deterministic models. It is particularly useful in the field of reverse engineering in systems biology, when one seeks to determine model parameters and noise properties as we show in the Results section, where we applied the approach to examples of increasing complexity and to the Hog1 signalling pathway.
对于分子生物学中的实际模型，需要考虑细胞和细胞内环境中的噪声。在本文中，我们提出了一种新颖的方法来测试表示受噪声影响的生物系统的非线性模型的有效性。我们的方法基于库什纳（Kushner）和奥克森达尔（Øksendal）的研究成果，并使用依赖高效求解器的计算技术。通过为系统在相空间中从特定集合出发的解轨迹的退出概率提供解析上界，我们可以将测量数据与该预测进行比较，并尝试使具有特定参数值或噪声特性的模型无效。因此，我们的方法补充了基于确定性模型的常用方法。正如我们在结果部分所示，当人们试图确定模型参数和噪声特性时，它在系统生物学的逆向工程领域特别有用，我们在该部分将该方法应用于复杂度不断增加的示例以及Hog1信号通路。
