比较化学反应网络:分类和算法的观点

L. Cardelli, M. Tribastone, Max Tschaikowski, Andrea Vandin
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引用次数: 23

摘要

我们研究了化学反应网络(crn)作为基于常微分方程语义的并发模型的核心语言。我们研究了比较两个CRN的问题,即在适当的初始条件选择下,决定源CRN的轨迹是否可以与目标CRN匹配。使用范畴框架,我们扩展并关联了基于CRN的结构(句法)和动态(语义)特性的模型比较方法,证明了它们的等价性。然后,我们提供了一种比较crn的算法,该算法相对于所有可能比较的基数在时间上线性运行。最后,我们将我们的结果应用于文献中的生物模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing Chemical Reaction Networks: A Categorical and Algorithmic Perspective
We study chemical reaction networks (CRNs) as a kernel language for concurrency models with semantics based on ordinary differential equations. We investigate the problem of comparing two CRNs, i.e., to decide whether the trajectories of a source CRN can be matched by a target CRN under an appropriate choice of initial conditions. Using a categorical framework, we extend and relate model-comparison approaches based on structural (syntactic) and on dynamical (semantic) properties of a CRN, proving their equivalence. Then, we provide an algorithm to compare CRNs, running linearly in time with respect to the cardinality of all possible comparisons. Finally, we apply our results to biological models from the literature.
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