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ecm_enzyme_cost_minimization

PURPOSE ^

ECM_ENZYME_COST_MINIMIZATION - Compute optimal flux-specific enzyme costs for given flux distribution

SYNOPSIS ^

function [c, u, u_cost, up, A_forward, mca_info, c_min, c_max, u_min, u_max, r, u_capacity, eta_energetic, eta_saturation] = ecm_enzyme_cost_minimization(network,r,v,ecm_options)

DESCRIPTION ^

 ECM_ENZYME_COST_MINIMIZATION - Compute optimal flux-specific enzyme costs for given flux distribution

 [c, u, u_cost, up, A_forward, mca_info, c_min, c_max, u_min, u_max, r, u_capacity, eta_energetic, eta_saturation] = ecm_enzyme_cost_minimization(network, e, v, ecm_options)

 Input 
   network       metabolic network structure (as in Metabolic Network Toolbox)
   r             Kinetic constants (from parameter balancing)
   v             flux mode
   ecm_options   options struct (for fields and default values, see 'ecm_default_options')

 Output
   c                 metabolite concentrations
   c.data            data vector (if provided)
   c.fixed           fixed concentration vector
   c.initial         initial solution vector 
   c.[SCORE]         1st column: result from optimising the score [SCORE]
                     other columns: possible sampled solutions
                     
   u                 enzyme levels (all enzymes)
   u.data            data vector
   u.[SCORE]         1st column: result from optimising the score [SCORE]
                     other columns: possible sampled solutions

   up                enzyme levels (only scored enzymes as defined by 
                                    ecm_scores.ind_scored_enzymes)
   up.[SCORE]        1st column: result from optimising the score [SCORE]
                     other columns: possible sampled solutions

   u_cost            sum of scored enzyme levels 
   u_cost.data       data value
   u_cost.[SCORE]    1st column: result from optimising the score [SCORE]
                     other columns: possible sampled solutions

   A_forward         reaction affinity (in flux direction)
   A_forward.initial    initial solution vector 
   A_forward.[SCORE] 1st column: result from optimising the score [SCORE]
                     other columns: possible sampled solutions

CROSS-REFERENCE INFORMATION ^

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