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首页> 外文期刊>Set-valued and variational analysis >Infection Time in Multistable Gene Networks. A Backward Stochastic Variational Inequality with Nonconvex Switch-Dependent Reflection Approach
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Infection Time in Multistable Gene Networks. A Backward Stochastic Variational Inequality with Nonconvex Switch-Dependent Reflection Approach

机译:多稳态基因网络中的感染时间。具有非凸开关相关反射方法的后向随机变分不等式

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摘要

We investigate a mathematical model associated to the infection time in multi-stable gene networks. The mathematical processes are of hybrid switch type. The switch is governed by pure jump modes and linked to DNA bindings. The differential component follows backward stochastic dynamics reflected in some mode-dependent nonconvex domains. First, we study the existence of solutions to the resulting stochastic variational inclusions, by reducing the model to a family of ordinary variational inclusions with generalized reflection in semiconvex domains. Second, by considering control-dependent drivers, we hint to some model-selection approach by embedding the controlled backward stochastic variational inclusion in a family of regular measures. Regularity and structural properties of these sets are given.
机译:我们研究了与多稳态基因网络中的感染时间相关的数学模型。数学过程是混合开关类型。该开关受纯跳跃模式控制,并与DNA结合相关。微分分量遵循某些模式相关的非凸域中反映的后向随机动力学。首先,通过将模型简化为在半凸域中具有广义反射的普通变分包含族,我们研究了所得随机变分包含的解的存在性。其次,通过考虑依赖控制的驱动程序,我们通过将受控的后向随机变分包含项嵌入到一系列常规量度中,来暗示一些模型选择方法。给出了这些集合的规则性和结构性质。

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