Evaluation of alternative model structures of metabolic systems: two case studies on model identification and validation

In the paper some quantitative criteria for evaluating alternative linear model structures are presented and applied to two metabolic systems. Linear time-invariant structured models and input/output descriptions are proposed for the two metabolic processes considered, bilirubin and riphamicin kinetics, and maximum likelihood parameter estimates are obtained from input/output test data. The considered criteria include model plausibility and quantitative measures, e.g. the F-test, Akaike information criterion and the inverse of the information matrix, which are based on the results of model identification from input/output data. The combined use of the Akaike criterion and of the inverse of the information matrix proves to be, in conjunction with model plausibility, a very reliable tool in the metabolic model structure determination.