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Special Feature: Complex Systems: From Chemistry to Systems Biology Special Feature: Internal coarse-graining of molecular systems

机译:特色:复杂系统:从化学到系统生物学特色:分子系统的内部粗粒度

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摘要

Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by posttranslational modifications and complex formation. Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules stipulating the (partial) contexts wherein specific protein–protein interactions occur. These contexts specify molecular patterns that are usually less detailed than molecular species. Yet, the execution of rule-based dynamics requires stochastic simulation, which can be very costly. It thus appears desirable to convert a rule-based model into a reduced system of differential equations by exploiting the granularity at which rules specify interactions. We present a formal (and automated) method for constructing a coarse-grained and self-consistent dynamical system aimed at molecular patterns that are distinguishable by the dynamics of the original system as posited by the rules. The method is formally sound and never requires the execution of the rule-based model. The coarse-grained variables do not depend on the values of the rate constants appearing in the rules, and typically form a system of greatly reduced dimension that can be amenable to numerical integration and further model reduction techniques.
机译:分子信号网络的建模者必须应对翻译后修饰和复合物形成所产生的蛋白质状态的组合爆炸。基于规则的模型为需要显式枚举系统所有可能分子种类的方法提供了强大的替代方法。此类模型由正式规则组成,这些规则规定了发生特定蛋白质间相互作用的(部分)环境。这些上下文指定了通常不如分子种类详细的分子模式。但是,基于规则的动力学的执行需要随机模拟,这可能会非常昂贵。因此,似乎希望通过利用规则指定交互作用的粒度将基于规则的模型转换为简化的微分方程系统。我们提出了一种正式的(自动的)方法,用于构建针对分子模式的粗粒且自洽的动力学系统,该分子模式可通过规则所假定的原始系统的动力学加以区分。该方法在形式上是合理的,并且不需要执行基于规则的模型。粗粒度变量不依赖于规则中出现的速率常数的值,并且通常形成尺寸可以大大减小的系统,该系统可以进行数值积分和进一步的模型简化技术。

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