cmb_options = cmb_default_options()
Returns matlab struct with default options for model balancing
Fields and default values are shown below
Algorithm settings
.run = 'my_run'; % name of estimation scenario (freely chosen by the user)
.kinetic_data_set = 'original'; % name of kinetic data set (freely chosen by the user)
.ecm_score = 'emc4cm'; % ECM score function, see 'help ecm_scores'
.initial_values_variant = 'average_sample'; % strategy for choosing initial values (see 'help cmb_estimation')
possible choices: 'average_sample', 'preposterior_mode',
'random', 'true_values', 'given_values'
.enzyme_score_type = 'interpolated'; % 'quadratic' (alpha=1), 'monotonic' (alpha =0), 'interpolated'
(only "monotonic" guarantees that MB is convex!)
.enzyme_score_alpha = 0.5; % interpolation parameter for enzyme_score_type='interpolated'
.parameterisation = 'Keq_KV_KM_KA_KI'; % options: 'Keq_KV_KM_KA_KI', 'KV_KM_KA_KI';
.use_kinetic_data = 'all'; % 'all', 'only_Keq_data', 'none'
.score = 'neg_log_posterior'; % options: 'neg_log_posterior', 'log_neg_log_posterior';
.use_gradient = 0; % flag: set opt.SpecifyObjectiveGradient = true in fmincon optimisation
.use_safe_optimisation = 1; % flag: run several rounds of optimisation (until convergence)
.random_seed = 1; % random seed for optimisation
Display and output options
.verbose = 0; % flag: verbose
.optim_display = 'off'; % flag: show graphical output during optimisation
.display = 1; % flag: display table with scores after each optimisation round
.show_graphics = 1; % flag: show graphics
.plot_true_vs_data = 0; % flag: show extra plots: true values against data values
(only in the case of artificial data)
.save_results = 1; % flag: save results to files
.save_graphics = 1; % flag: save graphics to files
Options for generating artificial data (see 'help cmb_model_artificial_data')
.use_artificial_noise = 0; % flag: generate artificial state data with noise
.use_kinetic_data_noise = 1; % flag: generate artificial kinetic data with noise
.prior_variant = 'original_prior'; original prior
'broad_prior' broad prior around original prior means
'broad_prior_around_zero' broad prior around 0 values
'prior_around_true_values' prior around true values (only for artificial data)
'broad_prior_around_true_values' broad prior around true values (only for artificial data)
Bounds and distributions for model variables
(Options to override the default values set in the prior table file)
.quantities.Keq.max new value for upper_bound(ind.Keq);
.quantities.Keq.mean_ln new value for prior_median_ln(ind.Keq);
.quantities.Keq.std_ln new value for prior_geostd_ln(ind.Keq);
.quantities.KV.min new value for lower_bound(ind.KV);
.quantities.KV.max new value for upper_bound(ind.KV);
.quantities.KV.mean_ln new value for prior_median_ln(ind.KV);
.quantities.KV.std_ln new value for prior_std_ln(ind.KV), default log(5);
.quantities.KM.min new value for lower_bound(ind.KM);
.quantities.KM.max new value for upper_bound(ind.KM);
.quantities.KM.mean_ln new value for prior_median_ln(ind.KM);
.quantities.KM.std_ln new value for prior_geostd_ln(ind.KM), default log(5 mM)
.quantities.KA.min new value for lower_bound(ind.KA);
.quantities.KA.max new value for upper_bound(ind.A);
.quantities.KA.mean_ln new value for prior_median_ln(ind.KA);
.quantities.KA.std_ln new value for prior_geostd_ln(ind.KA);
.quantities.KI.min new value for lower_bound(ind.KI);
.quantities.KI.max new value for upper_bound(ind.KI);
.quantities.KI.mean_ln new value for prior_median_ln(ind.KI);
.quantities.KI.std_ln new value for prior_geostd_ln(ind.KI);
.quantities.v.max new value for upper_bound(v), default 100 mM/s
.quantities.c.min new value for lower_bound(ind.c);
.quantities.c.max new value for upper_bound(ind.c);
.quantities.e.max new value for upper_bound(ind.u);
.quantities.Aforward.min new value for lower_bound(ind.A), default 0.0001 kJ/Mol
.quantities.Aforward.max new value for upper_bound(ind.A);
Distributions from which "true values" are drawn
.quantities.mu0.std default RT * log(5);
.metabolic_prior_c_geom_mean default 1 mM
.metabolic_prior_e_geom_mean default 0.001 mM
.metabolic_prior_c_geom_std default 10
.metabolic_prior_e_geom_std default 10
.data_kin_geom_std default 1.5
.data_V_geom_std default 1.2
.data_C_geom_std default 1.2
.data_E_geom_std default 1.2
Distributions for noise in artificial data
.metabolic_artificial_c_geom_std default 1.5;
.metabolic_artificial_e_geom_std default 1.5;