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Revision as of 04:50, 21 September 2009 (view source) Ebennett (Talk | contribs) (New page: function [MinimalGenomes, UnEssentialGeneLists]=FindMinimalGenomes(TheModel, NumberOfMinGenomes, FinalGrowthRate, InitialFilterK, NumberOfSteps) %NumberOfMinGenomes: Number of minimal ge...) ← Older edit		Latest revision as of 07:52, 18 October 2009 (view source) Ebennett (Talk | contribs) (Removing all content from page)
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-	function [MinimalGenomes, UnEssentialGeneLists]=FindMinimalGenomes(TheModel, NumberOfMinGenomes, FinalGrowthRate, InitialFilterK, NumberOfSteps)	+
-	%NumberOfMinGenomes: Number of minimal genomes you want the code to find (since there are many possible minimal genomes)	+
-	%InitialFilterK: This constant (<1) times the initial growth rate gives you the minimum survival rate acceptible for the first gene deletion iteration.	+
-	%FinalGrowthRate is what the final growth rate will be.  Lower values result in a worse final growth rate, but more genes can be deleted	+
-	%(resulting in a smaller allowable minimal genome).	+
-		+
-	disp('May take 5 mins per NumberOfMinGenomes (default is 1 list)')	+
-	solutionI=optimizeCbModel(TheModel);	+
-	fValueInitial = solutionI.f	+
-		+
-	switch nargin	+
-	case 1	+
-	f1 = fValueInitial*0.87	+
-	f2 = 0.3	+
-	n = 2  % n=2 results in 3 "steps (3 iterations of gene filtering)"	+
-	f3 = (f1-(f2)-0.001)/n	+
-	NumberOfMinGenomes=1;	+
-	case 2	+
-	f1 = fValueInitial*0.87	+
-	f2 = 0.3	+
-	n = 2	+
-	f3 = (f1-(f2)-0.001)/n	+
-	case 3	+
-	f1 = fValueInitial*0.87	+
-	f2 = FinalGrowthRate	+
-	n = 2	+
-	f3 = (f1-(f2)-0.001)/n	+
-	case 4	+
-	f1 = fValueInitial*InitialFilterK	+
-	f2 = FinalGrowthRate	+
-	n = 2	+
-	f3 = (f1-(f2)-0.001)/n	+
-	case 5	+
-	f1 = fValueInitial*InitialFilterK	+
-	f2 = FinalGrowthRate	+
-	n = NumberOfSteps-1	+
-	f3 = (f1-(f2)-0.001)/n	+
-	otherwise	+
-	error('Too many input arguments!')	+
-	end	+
-		+
-	MinimalGenomes=cell(1,NumberOfMinGenomes);	+
-	UnEssentialGeneLists=cell(1,NumberOfMinGenomes);	+
-	TheModelOriginal = TheModel;	+
-	w=1;	+
-		+
-	while w<=NumberOfMinGenomes	+
-	w	+
-		+
-	f=f1;	+
-		+
-	geneList=cell(1);	+
-	geneListTEST=cell(1);	+
-	d=1;	+
-		+
-	RandomGeneList=cell(1,length(TheModelOriginal.genes));	+
-	%this part shuffles the TheModel list for randomization	+
-	random=randperm(length(TheModel.genes))';	+
-	for x=(1:length(TheModel.genes))	+
-	RandomGeneList(x)=TheModelOriginal.genes(random(x));	+
-	end	+
-		+
-	while f>=f2	+
-	f	+
-		+
-	for c=(1:length(RandomGeneList))	+
-	match=zeros(length(RandomGeneList));	+
-	for a=(1:length(geneList))  %check if gene already on geneList. if so, skip analysis	+
-	if strcmp(geneList(a),RandomGeneList(c))==1	+
-	match(a)=1;	+
-	else	+
-	match(a)=0;	+
-	end	+
-	end	+
-		+
-	if sum(match)==0  %if gene does not exist in geneList yet, test its deletion	+
-	geneListTEST(d)=RandomGeneList(c);	+
-		+
-	deltamodel = deleteModelGenes(TheModelOriginal,geneListTEST);	+
-	solution = optimizeCbModel(deltamodel);	+
-		+
-	if solution.f>f %"if the deletion causes satisfactory growth, commit gene to geneList	+
-	geneList(d)=geneListTEST(d);	+
-	%F(d) = solution.f;	+
-	d=d+1;	+
-	end	+
-	end	+
-	end	+
-	disp('Genes Deleted So Far for this List is:'), disp(length(geneList))	+
-	f=f-f3;	+
-	end	+
-		+
-	UnEssentialGeneLists{w} = geneList';	+
-		+
-	%"inverts" the unessential list to obtain the essential list	+
-	InvertThis = UnEssentialGeneLists{w};	+
-	List2=TheModel.genes;	+
-		+
-	InvertedList=cell(1);	+
-		+
-	Match=zeros(length(List2));	+
-	for a=(1:length(InvertThis))	+
-	for b=(1:length(List2))	+
-	if strcmp(InvertThis(a), List2(b)) == 1	+
-	Match(b)=1;	+
-	end	+
-	end	+
-	end	+
-	d=1;	+
-		+
-	for c=(1:length(List2))	+
-	if Match(c)==0	+
-	InvertedList(d)=List2(c);	+
-	d=d+1;	+
-	end	+
-	end	+
-	MinimalGenomes{w}=InvertedList'	+
-		+
-	w=w+1;	+
-	end	+
-		+
-	%University of Alberta 2009 iGEM team	+
-	%Eric B	+

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Latest revision as of 07:52, 18 October 2009

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