Contents | ====================== |
cmb_basedir | |
cmb_default_options | cmb_options = cmb_default_options(flag_artificial) |
cmb_diagnostic_network_graphics | cmb_diagnostic_network_graphics(network, data, optimal, cmb_options, q_info, fignum, sample) |
cmb_display_scores | |
cmb_estimation | [optimal, gradient_V, init, time] = cmb_estimation(network, q_info, bounds, data, prior, preposterior, pp, V, cmb_options) |
cmb_filenames | filenames = cmb_filenames(model_name, prb, run, result_dir, network_sbml_file, flag_artificial) |
cmb_generate_artificial_data | [kinetics, prior, bounds, data, true, kinetic_data, state_data] = cmb_generate_artificial_data(network, cmb_options, q_info, e_init) |
cmb_graphics | |
cmb_log_posterior | [log_posterior,log_posterior_gradient] = cmb_log_posterior(y,pp,preposterior,V,cmb_options,q_info,verbose) |
cmb_make_bounds | |
cmb_make_pp | Structure pp contains the network and other information (needed to call ecm enzyme cost score function) |
cmb_make_prior | the following distribution can be improved (using the results of kinetic parameter balancing) |
cmb_model_and_data | [bounds, prior, init] = cmb_model_and_data(model, network, data, q_info, c_init, cmb_options) |
cmb_model_artificial_data | [network, bounds, prior, q_info, data, true, kinetic_data, state_data] = cmb_model_artificial_data(network_file, cmb_options, c_init, position_sbtab_file, constraint_sbtab_file) |
cmb_objective | % CURRENTLY NOT USED |
cmb_prepare_posterior | -------------------------------------------------------- |
cmb_prior_file | |
cmb_project_fluxes | [V, Vstd] = cmb_project_fluxes(V,Vstd,network,flag_project_fluxes) |
cmb_resourcedir | |
cmb_statistics | |
cmb_variables_to_log_posterior | f = cmb_variables_to_log_posterior(kinetics,X) |