diff --git a/doc/src/geckomat/utilities/ecFSEOF.html b/doc/src/geckomat/utilities/ecFSEOF.html index 5d80d73ae..eb327cf71 100644 --- a/doc/src/geckomat/utilities/ecFSEOF.html +++ b/doc/src/geckomat/utilities/ecFSEOF.html @@ -77,7 +77,7 @@

DESCRIPTION ^CROSS-REFERENCE INFORMATION ^

This function calls: +
  • getFluxTarget getFluxTarget
    • This function is called by: @@ -186,7 +186,7 @@

    SOURCE CODE ^% Simulate WT (100% growth) and forced (X% growth and the rest towards product): -0101 flux_WT = getFluxTarget(ecModel,targetRxn,csRxn); +0101 flux_WT = getFluxTarget(ecModel,params.bioRxn,targetRxn,1); 0102 0103 % Set values which are under solver tolerance 0104 flux_WT(flux_WT < 0 & ~enzRxns) = 0; @@ -194,7 +194,7 @@

    SOURCE CODE ^'Flux Scanning with Enforced Objective Function') 0108 for i = 1:length(alpha) -0109 flux_MAX = getFluxTarget(ecModel,targetRxn,csRxn,alpha(i)); +0109 flux_MAX = getFluxTarget(ecModel,params.bioRxn,targetRxn,alpha(i)); 0110 % Set values which are under solver tolerance 0111 flux_MAX(flux_MAX < 0 & ~enzRxns) = 0; 0112 flux_MAX(flux_MAX > 0 & enzRxns) = 0; diff --git a/doc/src/geckomat/utilities/getFluxTarget.html b/doc/src/geckomat/utilities/getFluxTarget.html index 6e6a93a2f..f790eec11 100644 --- a/doc/src/geckomat/utilities/getFluxTarget.html +++ b/doc/src/geckomat/utilities/getFluxTarget.html @@ -24,7 +24,7 @@

    PURPOSE ^getFluxTarget

    SYNOPSIS ^

    -
    function [maxFlux, minFlux] = getFluxTarget(model,targetRxn,csRxn,alpha,tolerance,modelAdapter)
    +
    function [maxFlux, minFlux] = getFluxTarget(model,bioRxn,targetRxn,alpha)

    DESCRIPTION ^

     getFluxTarget
@@ -37,15 +37,11 @@ 
    DESCRIPTION ^DESCRIPTION ^CROSS-REFERENCE INFORMATION ^
    
@@ -69,7 +65,7 @@ 
    CROSS-REFERENCE INFORMATION ^
 
 
 <h2><a name=SOURCE CODE ^
    
-
    0001 function [maxFlux, minFlux] = getFluxTarget(model,targetRxn,csRxn,alpha,tolerance,modelAdapter)
+
    0001 function [maxFlux, minFlux] = getFluxTarget(model,bioRxn,targetRxn,alpha)
 0002 % getFluxTarget
 0003 %
 0004 %   Function that performs a series of LP optimizations on an ecModel,
@@ -80,77 +76,58 @@ 
    SOURCE CODE ^%
 0010 % Input:
 0011 %   model           an ecModel in GECKO 3 format (with ecModel.ec structure).
-0012 %   targetRxn       rxn ID for the production target reaction, a exchange
-0013 %                   reaction is recommended.
-0014 %   csRxn           rxn ID for the main carbon source uptake reaction.
+0012 %   bioRxn          rxn ID for the biomass reaction.
+0013 %   targetRxn       rxn ID for the production target reaction, a exchange
+0014 %                   reaction is recommended.
 0015 %   alpha           scalling factor for desired suboptimal growth.
 0016 %                   (Optional, default 0.95)
-0017 %   tolerance       numerical tolerance for fixing bounds
-0018 %                   (Optional, default 1e-4)
-0019 %   modelAdapter    a loaded model adapter. (Optional, will otherwise use
-0020 %                   the default model adapter)
-0021 %
-0022 % Output:
-0023 %   minFlux         vector of minimum flux rates at minimum target production,
-0024 %                   corresponding to model.rxns
-0025 %   maxFlux         vector of maximum flux rates at maximum target production,
-0026 %                   corresponding to model.rxns
-0027 %
-0028 % Usage:
-0029 %   [maxFlux, minFlux] = simulateGrowth(ecModel,targetRxn,csRxn,alpha,tol)
+0017 %
+0018 % Output:
+0019 %   minFlux         vector of minimum flux rates at minimum target production,
+0020 %                   corresponding to model.rxns
+0021 %   maxFlux         vector of maximum flux rates at maximum target production,
+0022 %                   corresponding to model.rxns
+0023 %
+0024 % Usage:
+0025 %   [maxFlux, minFlux] = getFluxTarget(ecModel,bioRxn,targetRxn,alpha)
+0026 
+0027 if nargin < 4 || isempty(alpha)
+0028     alpha = 0.95;
+0029 end
 0030 
-0031 if nargin < 6 || isempty(modelAdapter)
-0032     modelAdapter = ModelAdapterManager.getDefault();
-0033     if isempty(modelAdapter)
-0034         error('Either send in a modelAdapter or set the default model adapter in the ModelAdapterManager.')
-0035     end
-0036 end
-0037 params = modelAdapter.getParameters();
-0038 
-0039 if nargin < 5 || isempty(tolerance)
-0040     tolerance = 1e-4;
-0041 end
-0042 
-0043 if nargin < 4 || isempty(alpha)
-0044     alpha = 0.95;
-0045 end
-0046 
-0047 % Get relevant rxn indexes
-0048 targetRxnIdx = getIndexes(model, targetRxn,'rxns');
-0049 csRxnIdx = getIndexes(model, csRxn,'rxns');
-0050 bioRxnIdx = getIndexes(model, params.bioRxn,'rxns');
-0051 
-0052 % Maximize growth and fix carbon source and suboptimal growth
-0053 model = setParam(model, 'obj', params.bioRxn, 1);
-0054 sol = solveLP(model);
-0055 model = setParam(model, 'var', csRxn, sol.x(csRxnIdx), tolerance);
-0056 model = setParam(model, 'lb', params.bioRxn, sol.x(bioRxnIdx) * (1-tolerance) * alpha);
-0057 
-0058 % If minimum fluxes are required get them
-0059 minFlux = [];
-0060 if nargout == 2
-0061     % Minimize target
-0062     model = setParam(model, 'obj', targetRxn, -1);
-0063     sol = solveLP(model);
-0064 
-0065     % Now fix min value for target and minimize proteins usage
-0066     model.lb(targetRxnIdx) = sol.x(targetRxnIdx) * (1-tolerance);
-0067     model = setParam(model, 'obj', 'prot_pool_exchange', 1);
-0068     minSol = solveLP(model,1);
-0069     minFlux = minSol.x;
-0070 end
-0071 
-0072 % Maximize target
-0073 model = setParam(model, 'obj', targetRxn, 1);
-0074 sol = solveLP(model);
-0075 
-0076 % Now fix max value for target and minimize proteins usage
-0077 model.lb(targetRxnIdx) = sol.x(targetRxnIdx) * (1-tolerance);
-0078 model = setParam(model, 'obj', 'prot_pool_exchange', 1);
-0079 maxSol = solveLP(model);
-0080 maxFlux = maxSol.x;
-0081 
-0082 end
    
+0031 % Fix a suboptimal alpha if equal to 1
+0032 if alpha == 1
+0033     alpha = 0.99;
+0034 end
+0035 
+0036 % Get relevant rxn indexes
+0037 bioRxnIdx    = getIndexes(model, bioRxn,'rxns');
+0038 poolIdx      = strcmpi(model.rxns, 'prot_pool_exchange');
+0039 
+0040 % Maximize growth and fix carbon source and suboptimal growth
+0041 model = setParam(model, 'obj', bioRxn, 1);
+0042 sol   = solveLP(model);
+0043 model = setParam(model, 'lb', bioRxn, sol.x(bioRxnIdx) * alpha);
+0044 
+0045 % Minimize prot_pool_exchange and fix
+0046 model = setParam(model, 'obj', 'prot_pool_exchange', 1);
+0047 sol   = solveLP(model);
+0048 model = setParam(model, 'lb', 'prot_pool_exchange', sol.x(poolIdx) * 1.01);
+0049 
+0050 % If minimum fluxes are required get them
+0051 minFlux = [];
+0052 if nargout == 2
+0053     % Minimize target
+0054     model = setParam(model, 'obj', targetRxn, -1);
+0055     minSol = solveLP(model);
+0056     minFlux = minSol.x;
+0057 end
+0058 
+0059 % Maximize target
+0060 model = setParam(model, 'obj', targetRxn, 1);
+0061 maxSol = solveLP(model);
+0062 maxFlux = maxSol.x;
+0063 end
    
 
    Generated by m2html © 2005
    
 
 
\ No newline at end of file
diff --git a/src/geckomat/utilities/ecFSEOF.m b/src/geckomat/utilities/ecFSEOF.m
index a29b267e2..00a70c2f8 100644
--- a/src/geckomat/utilities/ecFSEOF.m
+++ b/src/geckomat/utilities/ecFSEOF.m
@@ -98,7 +98,7 @@
 tolerance = 1e-4;
 
 % Simulate WT (100% growth) and forced (X% growth and the rest towards product):
-flux_WT = getFluxTarget(ecModel,targetRxn,csRxn);
+flux_WT = getFluxTarget(ecModel,params.bioRxn,targetRxn,1);
 
 % Set values which are under solver tolerance
 flux_WT(flux_WT < 0 & ~enzRxns) = 0;
@@ -106,7 +106,7 @@
 
 progressbar('Flux Scanning with Enforced Objective Function')
 for i = 1:length(alpha)
-    flux_MAX = getFluxTarget(ecModel,targetRxn,csRxn,alpha(i));
+    flux_MAX = getFluxTarget(ecModel,params.bioRxn,targetRxn,alpha(i));
     % Set values which are under solver tolerance
     flux_MAX(flux_MAX < 0 & ~enzRxns) = 0;
     flux_MAX(flux_MAX > 0 & enzRxns) = 0;
diff --git a/src/geckomat/utilities/getFluxTarget.m b/src/geckomat/utilities/getFluxTarget.m
index ba4308d97..be2059ed0 100644
--- a/src/geckomat/utilities/getFluxTarget.m
+++ b/src/geckomat/utilities/getFluxTarget.m
@@ -1,4 +1,4 @@
-function [maxFlux, minFlux] = getFluxTarget(model,targetRxn,csRxn,alpha,tolerance,modelAdapter)
+function [maxFlux, minFlux] = getFluxTarget(model,bioRxn,targetRxn,alpha)
 % getFluxTarget
 %
 %   Function that performs a series of LP optimizations on an ecModel,
@@ -9,15 +9,11 @@
 %
 % Input:
 %   model           an ecModel in GECKO 3 format (with ecModel.ec structure).
+%   bioRxn          rxn ID for the biomass reaction.
 %   targetRxn       rxn ID for the production target reaction, a exchange
 %                   reaction is recommended.
-%   csRxn           rxn ID for the main carbon source uptake reaction.
 %   alpha           scalling factor for desired suboptimal growth.
 %                   (Optional, default 0.95)
-%   tolerance       numerical tolerance for fixing bounds
-%                   (Optional, default 1e-4)
-%   modelAdapter    a loaded model adapter. (Optional, will otherwise use
-%                   the default model adapter)
 %
 % Output:
 %   minFlux         vector of minimum flux rates at minimum target production,
@@ -26,57 +22,42 @@
 %                   corresponding to model.rxns
 %
 % Usage:
-%   [maxFlux, minFlux] = simulateGrowth(ecModel,targetRxn,csRxn,alpha,tol)
-
-if nargin < 6 || isempty(modelAdapter)
-    modelAdapter = ModelAdapterManager.getDefault();
-    if isempty(modelAdapter)
-        error('Either send in a modelAdapter or set the default model adapter in the ModelAdapterManager.')
-    end
-end
-params = modelAdapter.getParameters();
-
-if nargin < 5 || isempty(tolerance)
-    tolerance = 1e-4;
-end
+%   [maxFlux, minFlux] = getFluxTarget(ecModel,bioRxn,targetRxn,alpha)
 
 if nargin < 4 || isempty(alpha)
     alpha = 0.95;
 end
 
+% Fix a suboptimal alpha if equal to 1
+if alpha == 1
+	alpha = 0.99;
+end
+
 % Get relevant rxn indexes
-targetRxnIdx = getIndexes(model, targetRxn,'rxns');
-csRxnIdx = getIndexes(model, csRxn,'rxns');
-bioRxnIdx = getIndexes(model, params.bioRxn,'rxns');
+bioRxnIdx    = getIndexes(model, bioRxn,'rxns');
+poolIdx      = strcmpi(model.rxns, 'prot_pool_exchange');
 
-% Maximize growth and fix carbon source and suboptimal growth 
-model = setParam(model, 'obj', params.bioRxn, 1);
-sol = solveLP(model);
-model = setParam(model, 'var', csRxn, sol.x(csRxnIdx), tolerance);
-model = setParam(model, 'lb', params.bioRxn, sol.x(bioRxnIdx) * (1-tolerance) * alpha);
+% Maximize growth and fix carbon source and suboptimal growth
+model = setParam(model, 'obj', bioRxn, 1);
+sol   = solveLP(model);
+model = setParam(model, 'lb', bioRxn, sol.x(bioRxnIdx) * alpha);
+
+% Minimize prot_pool_exchange and fix
+model = setParam(model, 'obj', 'prot_pool_exchange', 1);
+sol   = solveLP(model);
+model = setParam(model, 'lb', 'prot_pool_exchange', sol.x(poolIdx) * 1.01);
 
 % If minimum fluxes are required get them
 minFlux = [];
 if nargout == 2
     % Minimize target
     model = setParam(model, 'obj', targetRxn, -1);
-    sol = solveLP(model);
-
-    % Now fix min value for target and minimize proteins usage
-    model.lb(targetRxnIdx) = sol.x(targetRxnIdx) * (1-tolerance);
-    model = setParam(model, 'obj', 'prot_pool_exchange', 1);
-    minSol = solveLP(model,1);
+    minSol = solveLP(model);
     minFlux = minSol.x;
 end
 
 % Maximize target
 model = setParam(model, 'obj', targetRxn, 1);
-sol = solveLP(model);
-
-% Now fix max value for target and minimize proteins usage
-model.lb(targetRxnIdx) = sol.x(targetRxnIdx) * (1-tolerance);
-model = setParam(model, 'obj', 'prot_pool_exchange', 1);
 maxSol = solveLP(model);
 maxFlux = maxSol.x;
-
 end