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arXiv 1502.06992math.DSnlin.CG
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非遍历随机布尔网络的动力学区域

Dynamical regimes in non-ergodic random Boolean networks

Marco Villani, Davide Campioli, Chiara Damiani, Andrea Roli, Alessandro Filisetti, Roberto Serra

摘要:

随机布尔网络是一种遗传调控网络模型,已被证明能够描述生物学中的实验数据。它们不仅再现了细胞动力学中的重要现象,而且从理论的角度来看,它们也非常有趣,因为可以将它们的渐近行为从有序调整到无序。通常的方法将网络族作为一个整体来描述,或者通过静态的或者动态的测量。我们在这里表明,一个更详细的研究,系统的吸引子的属性的基础上,可以提供的信息,使得有可能预测更高精度的重要属性,如系统的响应基因敲除。引入了一套新的原则性措施,解释了这些网络的一些令人困惑的行为。这些结果并不局限于随机布尔网络模型,但它们是一般的,并保持任何离散模型表现出类似的动力学特性。

英文摘要:

Random boolean networks are a model of genetic regulatory networks that has proven able to describe experimental data in biology. They not only reproduce important phenomena in cell dynamics, but they are also extremely interesting from a theoretical viewpoint, since it is possible to tune their asymptotic behaviour from order to disorder. The usual approach characterizes network families as a whole, either by means of static or dynamic measures. We show here that a more detailed study, based on the properties of system's attractors, can provide information that makes it possible to predict with higher precision important properties, such as system's response to gene knock-out. A new set of principled measures is introduced, that explains some puzzling behaviours of these networks. These results are not limited to random Boolean network models, but they are general and hold for any discrete model exhibiting similar dynamical characteristics.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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