Comparison of notable characteristics in the machine and ensemble models.

<p>(A) Cumulative number of unique signaling complexes sampled by the machine and ensemble models (black and red, respectively) as a function of the number of independent simulations considered. We see that ensemble model generates a set of complexes approximately two orders of magnitude larger than the machine model over a range of 600 simulations. (B) Drift density among scaffold species in the validated machine model (n = 450) and 1000 machine models with randomized parameters (n = 7789) as compared to the data in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003278#pcbi-1003278-g003" target="_blank">Fig. 3C</a>. A large difference between the machine and ensemble models can be seen, with significantly higher mean drift in both the validated ensemble model and the set of randomized ensemble models (both comparisons have a significance of <i>p</i><10⁻⁵, see Section 2.4 in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003278#pcbi.1003278.s002" target="_blank">Text S1</a>). It is also notable that the largest drift value from the machine model is much lower than the smallest from the set of ensemble models with randomized parameters. The remaining heterogeneity observed in the machine model can be attributed to the presence of assembly intermediates and regulatory interactions.