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首页> 外文期刊>Journal of Mathematical Biology >Geometry and topology of parameter space: investigating measures of robustness in regulatory networks
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Geometry and topology of parameter space: investigating measures of robustness in regulatory networks

机译:参数空间的几何结构和拓扑:研究监管网络中的鲁棒性的度量

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摘要

The concept of robustness of regulatory networks has been closely related to the nature of the interactions among genes, and the capability of pattern maintenance or reproducibility. Defining this robustness property is a challenging task, but mathematical models have often associated it to the volume of the space of admissible parameters. Not only the volume of the space but also its topology and geometry contain information on essential aspects of the network, including feasible pathways, switching between two parallel pathways or distinct/disconnected active regions of parameters. A method is presented here to characterize the space of admissible parameters, by writing it as a semi-algebraic set, and then theoretically analyzing its topology and geometry, as well as volume. This method provides a more objective and complete measure of the robustness of a developmental module. As a detailed case study, the segment polarity gene network is analyzed.
机译:调节网络的健壮性概念与基因之间相互作用的性质以及模式维持或可再现性的能力密切相关。定义此鲁棒性是一项艰巨的任务,但是数学模型通常将其与可允许参数空间的大小相关联。不仅空间的大小,而且其拓扑结构和几何形状都包含有关网络基本方面的信息,包括可行的路径,两个并行路径之间的切换或参数的不同/断开的有效区域。这里提出一种方法来表征可允许参数的空间,方法是将其编写为半代数集,然后从理论上分析其拓扑结构,几何形状以及体积。此方法为开发模块的鲁棒性提供了更为客观和完整的度量。作为详细的案例研究,分析了片段极性基因网络。

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