Instead of asking whether we believe a model's conclusions, we should be asking whether we believe the model's assumptions.
We conducted detailed sensitivity analyses to determine whether our model conclusions would differ had we used different parameter values (Technical Appendix 3).
But filament flexibility is nevertheless important in determining the filament bundling and buckling behaviors in that model, ultimately effecting plasmid segregation competence in the model and the conclusions we reach from our simulations.
Therefore, with a view to extending model conclusions to other cell types, we sought to explore the behaviour of the key model readout (steady state protein expression level, p̄) in the wider range of plausible parameter values, including those found in cancer cells.
We emphasize that all these evolutionary rates are order-of-magnitude estimates, and that such estimates are suffcient for our model and the conclusions we derive from it.
However, we feel that excluding this variable from the models strengthens the conclusions we are able to draw from the models, as it provided for a significantly larger and more representative sample.
Model and conclusion: We present an analogy between two unrelated instabilities.
We show that the inclusion of spatial autocorrelation can affect model conclusions and, as a consequence, may influence management recommendations.
Finally, we conclude this paper on the lessons learnt from building such an ASM-only IGRF candidate model ("Conclusions" section).
Model conclusions can be very sensitive to these choices.
