other local sensitivity analysis, is that it is only predictive for small changes of reaction rates. However, the changes that result in disease states are usually large, and experimental parameter estimation can result in large uncertainty. Thus a global sensitivity analysis was also performed following the method described in [@Sahle2008New]. This calculates the maximal and minimal values of the sensitivity coefficients within a large space of parameter values. This technique is useful, for example, if there is uncertainty about the values of the model parameters as it reveals the possible range of control of each one given the uncertainty. All parameters were allowed to vary within $\pm$ 10% and the maximal and minimal control coefficients were measured (Tables \[table:MCA\], \[table:MCAHepc\] and \[table:MCAFlux\]).

In terms of the control of the labile iron pool (Table \[table:MCA\]), the reactions with highest control in the reference steady state are still the ones with highest control in the global case ([*i.e.*]{} when all parameters have an uncertainty of $\pm 10\%$). However TfR1 expression, TfR1 binding, TfR1 degradation, IRP expression and IRP degradation, which all have significant (but not the highest) control in the reference state, could have very low control in the global sense. On 