In stochastic (probabilistic) models, the evolution of a system over time is calculated using a "Master Equation" which also factors the external and internal noise / perturbations in order to more accurately replicate the behavior of a biological system (e.g. cell growth). I am unable to understand what is it, specifically, about the "Master Equation" that allows computational biologists to replicate a biological network with noise?

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    $\begingroup$ Welcome to the site. Perhaps it would be easier to answer if you pointed towards a paper or a course book where you found this reference. I have never heard of this Master Equation (but maybe this is specific to a sub-field or something) $\endgroup$ – llrs Mar 24 '19 at 19:50
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    $\begingroup$ @llrs: en.wikipedia.org/wiki/Master_equation I hadn't heard that particular term before, but it's the phenominological description of a non-stationary (i.e., evolving with time) process. $\endgroup$ – Devon Ryan Mar 24 '19 at 23:39
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    $\begingroup$ @mobs By "noise" here are you referring to the probabilistic change in state of individual members? Regarding perturbations, if you mean external perturbations then they're not always accounted for (they would need to be made explicit in the differential equations). $\endgroup$ – Devon Ryan Mar 24 '19 at 23:42

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