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Systematic component selection for gene-network refinement

机译:基因网络优化的系统组件选择

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Motivation: A quantitative description of interactions between cell components is a major challenge in Computational Biology. As a method of choice, differential equations are used for this purpose, because they provide a detailed insight into the dynamic behavior of the system. In most cases, the number of time points of experimental time series is usually too small to estimate the parameters of a model of a whole gene regulatory network based on differential equations, such that one needs to focus on subnetworks consisting of only a few components. For most approaches, the set of components of the subsystem is given in advance and only the structure has to be estimated. However, the set of components that influence the system significantly are not always known in advance, making a method desirable that determines both, the components that are included into the model and the parameters.
机译:动机:细胞组成之间相互作用的定量描述是计算生物学的主要挑战。作为一种选择方法,微分方程可用于此目的,因为它们提供了对系统动态行为的详细了解。在大多数情况下,实验时间序列的时间点数量通常太少,不足以根据微分方程估算整个基因调控网络的模型参数,因此人们只需要关注仅由几个组成部分组成的子网即可。对于大多数方法,子系统的组件集是预先给出的,只需要估计结构即可。但是,并不总是事先知道对系统有重大影响的组件集,因此需要一种方法来确定模型中包含的组件和参数。

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