To compensate for near extracellular concentrations of Ca2+ in this model we have scaled the influx parameter J stim with (1 − [Ca2+]/[Ca2+] ext ) in all the simulations.
To make them more comparable across models and data sets, we scaled the relative substitution rates so they refer the same unit of time, that in which we expect to see exactly one change per site.
To assess the proportional hazards assumptions of the Cox models, we examined scaled Schoenfeld residuals and found no evidence against proportionality.
To derive richer and more informative network models, we also scaled up the implementation to deal with a larger number of proteomic and phenotypic nodes (see 'Materials and methods' for details and comments on potential future opportunities in perturbation biology).
We scaled each model's output such that the average response to the positive 2-point glider was 1.
To get more physical insight into the model, we express scale factor in three useful forms [17, 18, 19, 20, 21, 22] (emergent, logamediate, and intermediate scenarios) under which the universe expands differently.
Before introducing a stochastic model, we apply scale time and population by using non-dimensional variables t = c b t ˜ and defining x = b a u and by defining k = a b c, we obtain d x ( t ) d t = k x ( t ) ( 1 − x ( t ) − ∫ 0 t x ( s ) d s ), x ( 0 ) = x 0. (1).
In our model we used scales taken from the COPSOQ [ 35] to consider psychosocial factors concentrating on quantitative demands, cognitive demands, influence at work, social support from colleagues and superiors, social relationship in the company, and job satisfaction.
