Application | Design variables (D) | Regressor matrix (X) | Response matrix (Y) | Test set used |
---|---|---|---|---|
Gene regulatory networks | 125 initial conditions for the three state variables X1, X2 and X3 (at time zero) in a 5^{3} FFD (dimensions: 125 × 3) | [D sin(D) cos(D)] |
The concatenated time series for the state variables X1, X2 and X3 (Y_{i} = 3 × 300 time points, i = 1 to nr. of observations) | 33% of the observations in D (randomly chosen), and the corresponding Y-values |
Mammalian circadian clock model |
Nine model parameters in an OMBR design using eight levels for each parameter (dimensions: 8192 × 9) | [D cross-terms of D D^{2}] |
16 state variable time series modelled separately (for each state variable Y_{i} = 200 time points, i = 1 to nr. of observations) | 8192 new parameter combinations generated by random Monte Carlo sampling (here the entire matrix D was used for calibration) and corresponding Y-values |
Mouse ventricular myocyte model |
Ten model parameters in a 3^{10} FFD (dimensions: 59049 × 10) | [D cross-terms of D D^{2}]* |
35 state variable time series modelled separately (for each state variable Y_{i} = 200 time points, i = 1 to nr. of observations)* | 33% of the observations in D that did not fail (randomly chosen), and the corresponding Y-values |