COMBOS2: an algorithm to the input–output equations of dynamic biosystems via Gaussian elimination
COMBOS2: an algorithm to the input–output equations of dynamic biosystems via Gaussian elimination
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DOI：
10.1080/16583655.2020.1776466
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发表时间：
2020-01
影响因子：
3.3
通讯作者：
Ali Kalami Yazdi;Mehdi Nadjafikhah;Joseph Distefano III
中科院分区：
文献类型：
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作者：
Ali Kalami Yazdi;Mehdi Nadjafikhah;Joseph Distefano III
微分代数(DA)方法目前被用于分析动态生物系统模型的结构可辨识性(SI)性质。这种方法的早期步骤需要找到等价的输入-输出(I/O)模型。最近一种基于Grbner基并嵌入到应用Combos中的寻找这些方程的方法相对较慢，有时甚至不成功，即使是对于中等大小的模型也是如此。在这篇文章中，我们提出了一个更快的算法，使用高斯消去法分析线性动态生物系统模型的子类。我们应用这种方法来寻找这些模型的最简单的全局SI参数组合，并表明它对简单到中等复杂性的线性生物系统模型有效。
Differential algebra (DA) methods are currently being exploited for analyzing dynamic biosystem models for their structural identifiability (SI) properties. An early step in this approach entails finding an equivalent input–output (I/O) model. A recent approach for finding these equations, based on Grbner bases and imbedded in the app COMBOS is relatively slow and sometimes unsuccessful, even for moderate size models. In this paper, we propose a faster algorithm, using a Gaussian elimination approach for analyzing the subclass of linear dynamic biosystem models. We apply this methodology to find the simplest set of globally SI parameter combinations of these models and show that it works effectively for linear biosystem models of simple to moderate complexity.