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Discrete-time models for gene transcriptional regulation networks

机译:基因转录调控网络的离散模型

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The recent finding of functional motifs (by Uri Alon an co-workers) in gene regulatory networks has provided an important interpretative tool for systems biology. Despite the available models are made of continuous-time ordinary differential equations, the experimental data needed to validate such motifs in living cells are inherently discrete in time. Moreover, the technology is currently very expensive, so that an accurate choice of a limited number of samples is mandatory. In this paper we investigate the dynamical properties of network motifs under sampling and provide simple rules for choosing the appropriate sampling rate which preserves peculiar dynamical features for the most common network motifs.
机译:基因调控网络中功能性基序的最新发现(由Uri Alon的一位同事)为系统生物学提供了重要的解释工具。尽管可用的模型是由连续时间的常微分方程组成的,但验证活细胞中此类基序所需的实验数据在时间上固有地是离散的。此外,该技术目前非常昂贵,因此必须精确选择有限数量的样本。在本文中,我们研究了采样条件下网络主题的动力学特性,并为选择合适的采样率提供了简单规则,该采样率保留了最常见的网络主题所特有的动态特征。

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