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| - | function [MinimalGenomes, UnEssentialGeneLists, Models] = FindMinimalGenomes(TheModel, NumberOfMinGenomes, FinalGrowthRate, IterationsPerList, FirstThreshold)
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| - | %NumberOfMinGenomes: Number of minimal genomes you want the code to find (since there are many possible minimal genomes)
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| - | %FinalGrowthRate: is what the final growth rate will apporximately be. Lower values result in a lower final
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| - | %growth rate, but this allows for more genes to be deleted (resulting in a smaller allowable minimal genome).
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| - | %FirstThreshold: This is the threshold growth rate for the first iteration of gene deletions.
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| - |
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| - | disp('May take 5 mins per NumberOfMinGenomes (default is 1 list)')
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| - | solutionI = optimizeCbModel(TheModel);
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| - | InitialGrowthRate = solutionI.f;
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| - |
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| - | %Input/Output Error Checking
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| - |
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| - | if nargout == 0
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| - | error('You must have at least 1 output argument! For example: MinGenomes = FindMinimalGenomes(model)')
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| - | end
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| - | if nargin >=3
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| - | if FinalGrowthRate > InitialGrowthRate
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| - | disp(['FinalGrowthRate (set by you): ' num2str(FinalGrowthRate)]);
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| - | error('The FinalGrowthRate must be less than the InitialGrowthRate')
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| - | end
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| - | end
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| - | if nargin >=4
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| - | if IterationsPerList < 1
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| - | error('IterationsPerList must be greater than or equal to 1!')
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| - | end
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| - | end
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| - | if nargin == 5
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| - | if FirstThreshold >= InitialGrowthRate
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| - | error('FirstThreshold must be less than the InitialGrowthRate')
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| - | end
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| - | end
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| - |
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| - | %Initialization of variables
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| - |
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| - | switch nargin
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| - | case 1
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| - | FinalGrowthRate = 0.2;
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| - | FirstThreshold = ((InitialGrowthRate-FinalGrowthRate)*0.87)+FinalGrowthRate;
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| - | n = 2; IterationsPerList = n+1 ; % n = 2 results in 3 iterations of gene filtering.
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| - | NumberOfMinGenomes = 1;
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| - | case 2
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| - | FinalGrowthRate = 0.2;
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| - | FirstThreshold = ((InitialGrowthRate-FinalGrowthRate)*0.87)+FinalGrowthRate;
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| - | n = 2; IterationsPerList = n+1 ;
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| - | case 3
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| - | FinalGrowthRate;
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| - | FirstThreshold = ((InitialGrowthRate-FinalGrowthRate)*0.87)+FinalGrowthRate;
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| - | n = 2; IterationsPerList = n+1;
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| - | case 4
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| - | if rem(IterationsPerList,1) ~= 0
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| - | error('IterationsPerList must be an integer')
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| - | end
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| - | FinalGrowthRate;
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| - | FirstThreshold = ((InitialGrowthRate-FinalGrowthRate)*0.87)+FinalGrowthRate;
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| - | if IterationsPerList == 1
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| - | n = 0.000000001; %Causes only 1 iteration & prevents division by 0 (which only Chuck Norris can do).
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| - | else
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| - | n = IterationsPerList-1;
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| - | end
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| - | case 5
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| - | if rem(IterationsPerList,1) ~= 0
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| - | error('IterationsPerList must be an integer')
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| - | end
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| - | FinalGrowthRate;
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| - | FirstThreshold;
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| - | if IterationsPerList == 1
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| - | n = 0.000000001; %to cause only 1 iteration & to prevent division by 0
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| - | else
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| - | n = IterationsPerList-1;
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| - | if FirstThreshold < FinalGrowthRate
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| - | error('FirstThreshold must be greater than FinalGrowthRate')
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| - | end
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| - | end
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| - | otherwise
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| - | error('Too many input arguments! Sorry, try again!')
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| - | end
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| - |
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| - | ThreshDrop = (FirstThreshold-(FinalGrowthRate)-0.0001)/n;
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| - | MinimalGenomes = cell(1,NumberOfMinGenomes);
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| - | UnEssentialGeneLists = cell(1,NumberOfMinGenomes);
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| - | TheModelOriginal = TheModel;
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| - | Models = cell(1);
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| - |
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| - | disp(['Initial Growth Rate is ' num2str(InitialGrowthRate)])
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| - | disp(['Final Growth Rate will be ~ ' num2str(FinalGrowthRate)])
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| - | disp(['First of ' num2str(IterationsPerList) ' growth rate thresholds is ' num2str(FirstThreshold)])
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| - | disp(['The growth rate threshold will drop by this amount for every iteration: ' num2str(ThreshDrop)])
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| - | disp(['Number of iterations for every list is ' num2str(IterationsPerList)])
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| - | w = 1;
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| - |
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| - | %Algorithm to find minimal genomes.
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| - |
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| - | while w<=NumberOfMinGenomes
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| - | disp(['FINDING MINIMAL GENOME LIST: ' num2str(w) ' of ' num2str(NumberOfMinGenomes)]);
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| - |
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| - | geneList = cell(1);
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| - | geneListTEST = cell(1);
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| - | d = 1;
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| - | k = 1;
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| - | f = FirstThreshold;
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| - |
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| - | %this part shuffles the TheModel list for randomization
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| - |
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| - | RandomGeneList = cell(1,length(TheModelOriginal.genes));
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| - | random = randperm(length(TheModel.genes))';
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| - | for x = (1:length(TheModel.genes))
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| - | RandomGeneList(x) = TheModelOriginal.genes(random(x));
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| - | end
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| - |
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| - | while f >= FinalGrowthRate
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| - | disp(['Performing iteration #' num2str(k) '. Threshold growth rate for this iteration of deletions is ' num2str(f) ' ...']);
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| - | for c = (1:length(RandomGeneList))
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| - | match = zeros(length(RandomGeneList));
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| - | for a = (1:length(geneList)) %check if gene already on geneList. if so, skip analysis
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| - | if strcmp(geneList(a),RandomGeneList(c)) == 1
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| - | match(a) = 1;
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| - | else
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| - | match(a) = 0;
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| - | end
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| - | end
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| - |
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| - | %This part decides whether or not to permanently knockout a gene
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| - |
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| - | if sum(match) == 0 %if gene does not exist in geneList yet, test its deletion
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| - | geneListTEST(d) = RandomGeneList(c);
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| - |
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| - | deltamodel = deleteModelGenes(TheModelOriginal,geneListTEST);
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| - | solution = optimizeCbModel(deltamodel);
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| - |
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| - | if solution.f > f %"if the deletion causes satisfactory growth, commit gene to geneList
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| - | geneList(d) = geneListTEST(d);
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| - | %F(d) = solution.f;
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| - | d = d+1;
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| - | end
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| - | end
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| - | end
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| - | disp(['Genes Deleted So Far for this List is: ' num2str(length(geneList))])
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| - | f = f-ThreshDrop;
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| - | k = k+1;
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| - | end
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| - |
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| - | UnEssentialGeneLists{w} = geneList';
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| - |
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| - | %This part "inverts" the unessential list of genes to obtain the essential list (the minimal genome).
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| - |
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| - | InvertThis = UnEssentialGeneLists{w};
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| - | WithThis = TheModel.genes;
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| - | InvertedList = cell(1);
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| - |
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| - | Match=zeros(length(WithThis));
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| - | for a = (1:length(InvertThis))
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| - | for b = (1:length(WithThis))
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| - | if strcmp(InvertThis(a), WithThis(b)) == 1
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| - | Match(b) = 1;
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| - | end
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| - | end
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| - | end
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| - |
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| - | d = 1;
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| - | for c=(1:length(WithThis))
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| - | if Match(c) == 0
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| - | InvertedList(d) = WithThis(c);
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| - | d = d+1;
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| - | end
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| - | end
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| - | MinimalGenomes{w} = InvertedList'
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| - |
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| - | if nargout > 2
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| - | Models{w} = deleteModelGenes(TheModelOriginal, geneList);
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| - | end
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| - | w = w+1;
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| - | end
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| - |
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| - | if nargout > 2
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| - | disp('Reassign a model of interest like this: modelMinimal = Models{3}, except replace "Models" with your 3rd output argument.')
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| - | end
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| - |
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| - | %University of Alberta 2009 iGEM Team
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| - | %Project BioBytes
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| - | %EricB
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