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Analytic theories of allometric scaling

机译:异度缩放的解析理论

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During the 13 years since it was first advanced, the fractal network theory (FNT), an analytic theory of allometric scaling, has been subjected to a wide range of methodological, mathematical and empirical criticisms, not all of which have been answered satisfactorily. FNT presumes a two-variable power-law relationship between metabolic rate and body mass. This assumption has been widely accepted in the past, but a growing body of evidence during the past quarter century has raised questions about its general validity. There is now a need for alternative theories of metabolic scaling that are consistent with empirical observations over a broad range of biological applications. In this article, we briefly review the limitations of FNT, examine the evidence that the two-variable power-law assumption is invalid, and outline alternative perspectives. In particular, we discuss quantum metabolism (QM), an analytic theory based on molecular-cellular processes. QM predicts the large variations in scaling exponent that are found empirically and also predicts the temperature dependence of the proportionality constant, issues that have eluded models such as FNT that are based on macroscopic and network properties of organisms.
机译:分形网络理论(FNT)自从它第一次被提出以来的13年间,就受到了广泛的方法论,数学和经验主义的批评,但并不是所有的方法都令人满意。 FNT假设代谢率和体重之间存在两个变量的幂律关系。该假设在过去已被广泛接受,但是在过去的25年中,越来越多的证据提出了对其一般有效性的质疑。现在需要与在广泛的生物学应用中的经验观察一致的新的代谢定标理论。在本文中,我们简要回顾了FNT的局限性,研究了二变量幂律假设无效的证据,并概述了其他观点。特别是,我们讨论了量子代谢(QM),一种基于分子-细胞过程的分析理论。 QM可以预测凭经验发现的缩放指数的巨大变化,还可以预测比例常数的温度依赖性,这些问题是基于有机体的宏观和网络特性而无法使用的诸如FNT的模型。

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