Feng D
Basser Department of Computer Science, University of Sydney, NSW, Australia.
Biomed Sci Instrum. 1990;26:193-200.
A single input/single output experiment design may not provide sufficient information to quantify a model of a complex biological system, and multiple input or multiple output experiment designs are often not feasible. An alternate approach is to perform feasible studies with different combinations of input/output ports one at a time, but their simultaneous mathematical analysis can become dimensionally unwieldy. In these cases, a graphical approach can be helpful. Cut set analysis of compartmental models is presented and contrasted with more conventional analysis approaches. It is shown that the complexity of computations is reduced using cut set analysis, especially as the complexity of the model is increased. A case study is presented on quantifying parameters of the enterohepatic subsystem in thyroid hormone distribution and metabolism, based on four different sets of rat experiments performed in the Biocybernetics Laboratory at UCLA.
单输入/单输出实验设计可能无法提供足够信息来量化复杂生物系统的模型，而多输入或多输出实验设计通常不可行。另一种方法是一次对输入/输出端口的不同组合进行可行的研究，但对它们进行同步数学分析在维度上可能会变得难以处理。在这些情况下，图形方法可能会有所帮助。本文介绍了隔室模型的割集分析，并将其与更传统的分析方法进行了对比。结果表明，使用割集分析可降低计算复杂度，尤其是随着模型复杂度的增加。基于在加州大学洛杉矶分校生物控制论实验室进行的四组不同大鼠实验，给出了一个关于量化甲状腺激素分布和代谢中肠肝子系统参数的案例研究。
