There's a lot going on in biology at present, in many different areas. A lot of activity has to do with various aspects of computation. Certain algorithms or algorithmic templates have been identified which are reused across many vastly different domains. For instance, evolution, as a general principle, takes place among genes, among immune system molecules and, more controversially, among spatio-temporal neural firing patterns within the brain ([Calvin 1996], [Edelman 1988]). As another example, consider the Baldwin effect, whereby phenotypic plasticity smooths out the fitness landscape and may accelerate genotypic evolution, operates at vastly different scales, from bacteria to mammals [Dawkins 1982, chapter 9]. As a final example, note how modularization appears in so many different contexts in biology: the modularization introduced by cellular organelles, by the organs of an animal, by the areas of the cortex. Also of note is that modularization in biology is almost always leaky.
To an interested outside observer, reading or even browsing the standard cellular biology textbook [Alberts et al. 2002] brings a surprise at every page, to the effect that “Wow, I had no idea we knew how this works!”. If in addition the reader is interested in the nature and principles of computation, then the surprises are compounded by the feeling that much of what happens in a cell has to do with... computation.
The particular aspects of cellular biology which have been singled out as “computationally relevant” are given later, in Biological Inspiration. Most of them are easily accessible in the first quarter of the textbook cited above, which describes them from a biology perspective with the occasional computer analogy:
“The Regulation of Cdk and Src Protein Kinases Shows How a Protein Can Function as a Microchip” [Alberts et al. 2002, title page 179].
How does all this relate to Monod? A goal of Monod is to provide a practical test bed for computational analogues of some of the mechanisms identified as computationally relevant. Monod allows the user to vary operational parameters or to entirely turn off certain features in order to ascertain the impact on the computational ability of the model. For example, what is the impact of various degrees of modularization on the model? What is the significance of leakiness?