Simulation results are compared to additional measurements on the FPGA platform, which led to a further refinement of our system model.
Compared to model 1, model 2 has additional control variables, including sex, age, marital status, and smoking.
Given that unique initiating events in the tumor models should cause characteristic responses associated with the tumor initiating event, we used SAM to identify genes significantly altered within each model compared to all other models (Additional file 2).
Hence, we expect a richer set of gene frequency distributions predicted by model B compared to model A. Additional file 1: Figure S3 shows gene frequency distributions computed for different combinations of the parameters θ0 and β.
In all four cases of incongruence, and independent of the used age estimation, the evidence ratio [ 46] is generally higher in the stratified model when compared to unconstrained model (Additional file 1: Table S2).
This simple model was also compared to two models with additional free parameters: (a) a leaky averaging model that implemented an exponantial moving average when calculating the absolute integrated value of each bandit, (b) a leaky averaging model, in which the initial value of the reference (v prior ) was a free parameter.
The model logit(dexp) = age + per provided similar parameter estimates when compared to model averaging (Additional file 3).
The microscopic model incorporates an essential additional feature compared to previous models for bundle dynamics as it takes into account effects of filament assembly and disassembly, in particular, treadmilling.
Recent literature suggests that models that have been previously used to determine the additional LOS in hospital due to infection overestimated the additional LOS, compared to newer statistical models [ 5- 10].
