Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
J Appl Physiol (1985). 2011 May;110(5):1466-72. doi: 10.1152/japplphysiol.01289.2010. Epub 2011 Feb 3.
Multi-scale modeling of biological systems has recently become fashionable due to the growing power of digital computers as well as to the growing realization that integrative systems behavior is as important to life as is the genome. While it is true that the behavior of a living organism must ultimately be traceable to all its components and their myriad interactions, attempting to codify this in its entirety in a model misses the insights gained from understanding how collections of system components at one level of scale conspire to produce qualitatively different behavior at higher levels. The essence of multi-scale modeling thus lies not in the inclusion of every conceivable biological detail, but rather in the judicious selection of emergent phenomena appropriate to the level of scale being modeled. These principles are exemplified in recent computational models of the lung. Airways responsiveness, for example, is an organ-level manifestation of events that begin at the molecular level within airway smooth muscle cells, yet it is not necessary to invoke all these molecular events to accurately describe the contraction dynamics of a cell, nor is it necessary to invoke all phenomena observable at the level of the cell to account for the changes in overall lung function that occur following methacholine challenge. Similarly, the regulation of pulmonary vascular tone has complex origins within the individual smooth muscle cells that line the blood vessels but, again, many of the fine details of cell behavior average out at the level of the organ to produce an effect on pulmonary vascular pressure that can be described in much simpler terms. The art of multi-scale lung modeling thus reduces not to being limitlessly inclusive, but rather to knowing what biological details to leave out.
由于数字计算机功能日益强大，以及人们日益认识到整合系统行为对于生命与基因组同样重要，生物系统的多尺度建模近来变得非常流行。虽然生物体的行为最终必须归因于其所有组成部分及其无数相互作用，但试图将其全部编排在模型中会忽略从理解系统组件在一个尺度上的集合如何协同产生更高层次上定性不同的行为中获得的见解。因此，多尺度建模的本质不在于包含所有可以想象的生物学细节，而在于明智地选择适合所建模尺度的涌现现象。这些原则在最近对肺的计算模型中得到了体现。例如，气道反应性是气道平滑肌细胞内分子水平上的事件在器官水平上的表现，但没有必要援引所有这些分子事件来准确描述细胞的收缩动力学，也没有必要援引在细胞水平上观察到的所有现象来解释乙酰甲胆碱挑战后发生的整个肺功能变化。同样，血管平滑肌细胞内的血管紧张度调节起源复杂，但在器官水平上，许多细胞行为的细节会平均化，从而对肺动脉压产生影响，这种影响可以用更简单的术语来描述。因此，多尺度肺建模的艺术不在于无限包容，而在于知道要忽略哪些生物学细节。
