European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK.
Gene. 2013 Apr 10;518(1):70-7. doi: 10.1016/j.gene.2012.11.084. Epub 2012 Dec 21.
The paper proposes a hybrid system based approach for modelling of intracellular networks and introduces a restricted subclass of hybrid systems - HSM - with an objective of still being able to provide sufficient power for the modelling of biological systems, while imposing some restrictions that facilitate analysis of systems described by such models. The use of hybrid system based models has become increasingly popular, likely due to the facts that: 1) they provide sufficiently powerful mathematical formalism to describe biological processes of interest and do it in a 'natural way' from the biological perspective; 2) there are well established mathematical techniques as well as supporting software tools for analysing such models. However often these models are very dependent on the quantitative parameters of the system (concentrations of proteins, their growth functions etc.) that are seldom exactly known, instead of more limited information of the system that can be observed in practice (directions of change in concentrations, but not the exact values etc.). As a result these models may work well for simulation of the system (prediction of its state starting from some initial conditions), but are too complicated for prediction of all possible qualitatively different behaviours a modelled system might have. With HSM we try to propose a hybrid system based formalism that is still sufficiently powerful for description of biological systems, while being as restricted as possible to facilitate the analysis of the systems described. We separate between the quantitative system parameters and their qualitative values that can be observed in practice. For HSM we provide an algorithm that analyses the system without the need to know the exact parameter values. We apply our model and analysis methods to a well-studied gene network of λ-phage. The phage has two well-known qualitatively different behaviours - lysis and lysogeny. We show that our model has an attractor structure that corresponds well to these two behaviours and that these are the only stable behaviours that can be exhibited by the system. The algorithm also generates (in principle biologically verifiable) hypotheses about the mutations of λ-phage that should change its observable behaviour.
本文提出了一种基于混合系统的方法来对细胞内网络进行建模,并引入了混合系统的一个受限子类——HSM,目的是在为所描述的系统建模提供足够的能力的同时,施加一些限制,以便于分析这些模型。基于混合系统的模型的使用变得越来越流行,可能是因为以下事实:1)它们提供了足够强大的数学形式来描述感兴趣的生物过程,并且从生物学的角度来看是以“自然的方式”来描述的;2)有成熟的数学技术和支持软件工具来分析此类模型。然而,这些模型通常非常依赖于系统的定量参数(蛋白质的浓度、它们的生长函数等),这些参数很少是完全已知的,而是依赖于系统在实践中可以观察到的更有限的信息(浓度变化的方向,但不是确切值等)。因此,这些模型可能在系统的模拟(根据某些初始条件预测系统的状态)方面效果很好,但对于预测建模系统可能具有的所有定性不同的行为来说过于复杂。通过 HSM,我们尝试提出一种基于混合系统的形式主义,它仍然足够强大,可以用于描述生物系统,同时尽可能地限制它,以方便分析所描述的系统。我们将系统的定量参数与其在实践中可以观察到的定性值分开。对于 HSM,我们提供了一种无需知道确切参数值即可分析系统的算法。我们将我们的模型和分析方法应用于研究得很好的 λ-噬菌体基因网络。噬菌体有两种众所周知的定性不同的行为——裂解和溶原性。我们表明,我们的模型具有与这两种行为相对应的吸引子结构,并且这些是系统能够表现出的唯一稳定行为。该算法还生成了(原则上可以通过生物学验证的)关于 λ-噬菌体突变的假设,这些突变应该会改变其可观察到的行为。