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Learning from Noise: How Observing Stochasticity May Aid Microbiology
Trends in Microbiology ( IF 14.0 ) Pub Date : 2018-03-09 , DOI: 10.1016/j.tim.2018.02.003
Ariel Amir , Nathalie Q. Balaban

For many decades, the wedding of quantitative data with mathematical modeling has been fruitful, leading to important biological insights. Here, we review some of the ongoing efforts to gain insights into problems in microbiology – and, in particular, cell-cycle progression and its regulation – through observation and quantitative analysis of the natural fluctuations in the system. We first illustrate this idea by reviewing a classic example in microbiology – the Luria–Delbrück experiment – and discussing how, in that case, useful information was obtained by looking beyond the mean outcome of the experiment, but instead paying attention to the variability between replicates of the experiment. We then switch gears to the contemporary problem of cell cycle progression and discuss in more detail how insights into cell size regulation and, when relevant, coupling between the cell cycle and the circadian clock, can be gained by studying the natural fluctuations in the system and their statistical properties. We end with a more general discussion of how (in this context) the correct level of phenomenological model should be chosen, as well as some of the pitfalls associated with this type of analysis. Throughout this review the emphasis is not on providing details of the experimental setups or technical details of the models used, but rather, in fleshing out the conceptual structure of this particular approach to the problem. For this reason, we choose to illustrate the framework on a rather broad range of problems, and on organisms from all domains of life, to emphasize the commonality of the ideas and analysis used (as well as their differences).



中文翻译:

从噪声中学习:观察随机性如何帮助微生物学

数十年来,定量数据与数学建模的结合取得了丰硕的成果,从而带来了重要的生物学见解。在这里,我们将通过观察和定量分析系统中的自然波动,回顾一些正在进行的努力,以深入了解微生物学问题,尤其是细胞周期进程及其调控。我们首先通过回顾微生物学的一个经典例子-Luria-Delbrück实验,并讨论在那种情况下如何通过超越平均值来获得有用信息来说明这一想法。实验结果,但要注意实验重复之间的差异。然后,我们将注意力转向细胞周期进展的当代问题,并更详细地讨论如何通过研究系统中的自然波动来获得对细胞大小调节的见解,以及在相关时如何了解细胞周期与生物钟之间的耦合。他们的统计属性。我们以更广泛的讨论作为结束,讨论应如何(在此情况下)选择正确的现象学模型水平,以及与这种类型的分析相关的一些陷阱。在整个审查过程中,重点不是提供实验设置的细节或所用模型的技术细节,而是充实这种解决问题的特殊方法的概念结构。出于这个原因,我们选择说明范围广泛的问题以及生命各个领域的有机体的框架,以强调所使用的思想和分析(以及它们之间的差异)的共性。

更新日期:2018-03-09
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