FSEOF
Implements the Flux Scanning based on Enforced Objective Flux algorithm.
Input:
model a model structure
biomassRxn string with reaction ID of the biomass formation or
growth reaction
targetRxn string with reaction ID of target reaction
iterations numeric indicating number of iterations (optional,
default 10)
coefficient numeric indicating ratio of optimal target reaction
flux, must be less than 1 (optional, default 0.9)
outputFile string with output filename (optional, default prints
to command window)
Output:
targets structure with information for identified targets
logical logical array indicating whether a model reaction was
identified as target by FSEOF
slope numeric array with FSEOF slopes for target reactions
This function writes an tab-delimited file or prints to command window.
If an output has been specified (targets), it will also generate a
structure indicating for each model reaction whether it is identified by
FSEOF as a target and the slope of the reaction when switching from
biomass formation to product formation.
Usage: targets = FSEOF(model, biomassRxn, targetRxn, iterations,...
coefficient, outputFile)0001 function targets=FSEOF(model,biomassRxn,targetRxn,iterations,coefficient,outputFile) 0002 % FSEOF 0003 % Implements the Flux Scanning based on Enforced Objective Flux algorithm. 0004 % 0005 % Input: 0006 % model a model structure 0007 % biomassRxn string with reaction ID of the biomass formation or 0008 % growth reaction 0009 % targetRxn string with reaction ID of target reaction 0010 % iterations numeric indicating number of iterations (optional, 0011 % default 10) 0012 % coefficient numeric indicating ratio of optimal target reaction 0013 % flux, must be less than 1 (optional, default 0.9) 0014 % outputFile string with output filename (optional, default prints 0015 % to command window) 0016 % 0017 % Output: 0018 % targets structure with information for identified targets 0019 % logical logical array indicating whether a model reaction was 0020 % identified as target by FSEOF 0021 % slope numeric array with FSEOF slopes for target reactions 0022 % 0023 % This function writes an tab-delimited file or prints to command window. 0024 % If an output has been specified (targets), it will also generate a 0025 % structure indicating for each model reaction whether it is identified by 0026 % FSEOF as a target and the slope of the reaction when switching from 0027 % biomass formation to product formation. 0028 % 0029 % Usage: targets = FSEOF(model, biomassRxn, targetRxn, iterations,... 0030 % coefficient, outputFile) 0031 0032 biomassRxn=char(biomassRxn); 0033 targetRxn=char(targetRxn); 0034 0035 if nargin<4 0036 iterations=10; 0037 coefficient=0.9; 0038 end 0039 0040 if nargin <5 0041 coefficient=0.9; 0042 end 0043 0044 if nargin == 6 0045 output=1; 0046 else 0047 output=0; 0048 end 0049 0050 %Find out the maximum theoretical yield of target reaction 0051 model=setParam(model,'obj',targetRxn,1); 0052 sol=solveLP(model,1); 0053 targetMax=sol.f*coefficient; % 90 percent of the theoretical yield 0054 0055 model=setParam(model,'obj',biomassRxn,1); 0056 0057 fseof.results=zeros(length(model.rxns),iterations); 0058 fseof.target=zeros(length(model.rxns),1); 0059 rxnDirection=zeros(length(model.rxns),1); 0060 0061 %Enforce objective flux iteratively 0062 for i=1:iterations 0063 n=i*targetMax/iterations; 0064 model=setParam(model,'lb',targetRxn,n); 0065 0066 sol=solveLP(model,1); 0067 0068 fseof.results(:,i)=sol.x; 0069 0070 %Loop through all fluxes and identify the ones that increased upon the 0071 %enforced objective flux 0072 for j=1:length(fseof.results) 0073 if fseof.results(j,1) > 0 %Check the positive fluxes 0074 0075 if i == 1 %The initial round 0076 rxnDirection(j,1)=1; 0077 fseof.target(j,1)=1; 0078 else 0079 0080 if (fseof.results(j,i) > fseof.results(j,i-1)) & fseof.target(j,1) 0081 fseof.target(j,1)=1; 0082 else 0083 fseof.target(j,1)=0; 0084 end 0085 end 0086 0087 elseif fseof.results(j,1) < 0 %Check the negative fluxes 0088 0089 if i == 1 %The initial round 0090 rxnDirection(j,1)=-1; 0091 fseof.target(j,1)=1; 0092 else 0093 if (fseof.results(j,i) < fseof.results(j,i-1)) & fseof.target(j,1) 0094 fseof.target(j,1)=1; 0095 else 0096 fseof.target(j,1)=0; 0097 end 0098 end 0099 0100 end 0101 0102 end 0103 end 0104 0105 %Generating output 0106 formatSpec='%s\t%s\t%s\t%s\t%s\t%s\t%s\n'; 0107 if output == 1 %Output to a file 0108 outputFile=char(outputFile); 0109 fid=fopen(outputFile,'w'); 0110 fprintf(fid,formatSpec,'Slope','rowID','Enzyme ID','Enzyme Name','Subsystems','Direction','Gr Rule'); 0111 else %Output to screen 0112 fprintf(formatSpec,'Slope','rowID','Enzyme ID','Enzyme Name','Subsystems','Direction','Gr Rule'); 0113 end 0114 0115 for num=1:length(fseof.target) 0116 if fseof.target(num,1) == 1 0117 A0=num2str(abs(fseof.results(num,iterations)-fseof.results(num,1))/abs(targetMax-targetMax/iterations)); %Slope calculation 0118 A1=num2str(num); %row ID 0119 A2=char(model.rxns(num)); %enzyme ID 0120 A3=char(model.rxnNames(num)); %enzyme Name 0121 if isfield(model,'subSystems') && ~isempty(model.subSystems{num}); 0122 A4=char(strjoin(model.subSystems{num,1},';')); %Subsystems 0123 else 0124 A4=''; 0125 end 0126 A5=num2str(model.rev(num)*rxnDirection(num,1)); %reaction Dirction 0127 A6=char(model.grRules(num)); %Gr Rule 0128 if output == 1 %Output to a file 0129 fprintf(fid,formatSpec,A0,A1,A2,A3,A4,A5,A6); 0130 else %Output screen 0131 fprintf(formatSpec,A0,A1,A2,A3,A4,A5,A6); 0132 end 0133 end 0134 end 0135 0136 if output == 1 %Output to a file 0137 fclose(fid); 0138 end 0139 0140 if nargout == 1 0141 targets.logical=logical(fseof.target); 0142 targets.slope=abs(fseof.results(:,iterations)-fseof.results(:,1))/abs(targetMax-targetMax/iterations); %Slope calculation 0143 end 0144 end