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Temporal constraints of a gene regulatory network: Refining a qualitative simulation

机译:基因调控网络的时间限制:完善定性模拟

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The modelling of gene regulatory networks (GRNs) has classically been addressed through very different approaches. Among others, extensions of Thomas's asynchronous Boolean approach have been proposed, to better fit the dynamics of biological systems: genes may reach different discrete expression levels, depending on the states of other genes, called the regulators: thus, activations and inhibitions are triggered conditionally on the proper expression levels of these regulators. In contrast, some fine-grained propositions have focused on the molecular level as modelling the evolution of biological compound concentrations through differential equation systems. Both approaches are limited. The first one leads to an oversimplification of the system, whereas the second is incapable to tackle large GRNs. In this context, hybrid paradigms, that mix discrete and continuous features underlying distinct biological properties, achieve significant advances for investigating biological properties. One of these hybrid formalisms proposes to focus, within a GRN abstraction, on the time delay to pass from a gene expression level to the next. Until now, no research work has been carried out, which attempts to benefit from the modelling of a GRN by differential equations, converting it into a multi-valued logical formalism of Thomas, with the aim of performing biological applications. This paper fills this gap by describing a whole pipelined process which orchestrates the following stages: (i) model conversion from a piece-wise affine differential equation (PADE) modelization scheme into a discrete model with focal points, (ii) characterization of subgraphs through a graph simplification phase which is based on probabilistic criteria, (iii) conversion of the subgraphs into parametric linear hybrid automata, (iv) analysis of dynamical properties (e.g. cyclic behaviours) using hybrid model-checking techniques. The present work is the outcome of a methodological investigation launched to cope with the GRN responsible for the reaction of Escherichia coli bacterium to carbon starvation. As expected, we retrieve a remarkable cycle already exhibited by a previous analysis of the PADE model. Above all, hybrid model-checking enables us to infer temporal properties, whose biological signification is then discussed.
机译:传统上,基因调节网络(GRN)的建模是通过非常不同的方法来解决的。其中,有人提出了Thomas异步布尔方法的扩展,以更好地适应生物系统的动态:基因可能达到不同的离散表达水平,这取决于称为调节子的其他基因的状态:因此,激活和抑制是有条件地触发的这些调节子的正确表达水平。相反,一些细粒度的命题集中在分子水平上,通过微分方程系统模拟生物化合物浓度的变化。两种方法都有局限性。第一个导致系统的过于简化,而第二个则无法解决大型GRN。在这种情况下,混合范式混合了不同生物学特性下的离散和连续特征,在研究生物学特性方面取得了重大进展。这些混合形式主义中的一种提议在GRN抽象中集中于从基因表达水平传递到下一个表达水平的时间延迟。迄今为止,还没有进行过任何研究工作,试图从微分方程的GRN建模中受益,并将其转换为Thomas的多值逻辑形式主义,以进行生物学应用。本文通过描述安排以下阶段的整个流水线过程来填补这一空白:(i)将模型从分段仿射微分方程(PADE)建模方案转换为具有焦点的离散模型,(ii)通过一个基于概率标准的图形简化阶段,(iii)将子图转换为参数线性混合自动机,(iv)使用混合模型检查技术分析动力学特性(例如循环行为)。本工作是为应对负责大肠杆菌细菌对碳饥饿的反应的GRN而开展的方法学研究的结果。不出所料,我们检索了先前对PADE模型的分析已经显示出的显着周期。最重要的是,混合模型检查使我们能够推断时间特性,然后讨论其生物学意义。

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