Almirantis Y
Institute of Biology, NRC Demokritos, Athens, Greece.
Comput Chem. 2000 Mar;24(2):159-70. doi: 10.1016/s0097-8485(99)00057-1.
Turing's original reaction network is systematically studied, particularly in what concerns: (a) Its ability to produce patterns in a predictable way. (b) The feasibility of its concentration-independent sink term. Despite the widely accepted view that Turing's original model presents some inherent inability to produce regular structures, the pattern formation properties of this model are found to obey the predictions of the corresponding Linear Stability Analysis in the one-dimension and in 'small' two-dimensional systems. An 'Enzymatic' variation of the original Turing's Model is introduced, where the unrealistic sink term is substituted by an enzymatic degradation. It seems that reaction networks of this type can inspire a promising search for chemical or biochemical experimental systems with pattern formation properties, even in the absence of high non-linearities. It is pointed out that temporal oscillations, impossible for the original Turing's Model, are stable and persistent in its Enzymatic variation.
图灵最初的反应网络得到了系统研究，特别是在以下方面：(a) 以可预测方式产生模式的能力。(b) 其浓度无关汇项的可行性。尽管人们普遍认为图灵的原始模型在产生规则结构方面存在一些内在缺陷，但该模型的模式形成特性在一维和“小”二维系统中符合相应线性稳定性分析的预测。引入了原始图灵模型的一种“酶促”变体，其中不现实的汇项被酶促降解所取代。即使在没有高度非线性的情况下，这种类型的反应网络似乎也能激发对具有模式形成特性的化学或生化实验系统的有前景的探索。需要指出的是，原始图灵模型不可能出现的时间振荡在其酶促变体中是稳定且持续的。
