Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

Results from an experiment of combining LHS and genetic algorithm (GA) showed that 10 3 of LHS sampling followed by 100 generations of GA optimization yielded a similar set of kinetic motifs for NFBLB (Additional file 1 : Table S1), suggesting that optimization can help to find more solutions from a smaller initial parameter set, but in this case the hybrid approach did not reduce the computational cost (since it also needed a total of 10 5 model evaluations), and could miss some of the marginally significant motifs (Additional file 1 : Table S1).

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The results, summarized in Table 2 , indicate that three kinetic parameters, K AC , K FBB and K FCC , were highly significant in improving sensitivity scores, and six kinetic parameters, k BA , k FBB , K AB , K AC , K BA and K FCC , were highly significant in improving precision scores.

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