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COBRAmodels:fire:code headers:art: add tutorials
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‎src/design/TrimGdel/GRPRchecker.m

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function [GR ,PR] = GRPRchecker(model, targetMet, givenGvalue)
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function [GR ,PR] = GRPRchecker(model, targetMet, gvalue)
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% GRPRchecker calculates the maximum GR and the minimu PR
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% under the GR maximization when a constraint-based model, a target
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% metabolite, and a gene deletion stratety are given.
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%
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% function [GR, PR]
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% = GRPRchecker(model, targetMet, givenGvalue)
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% USAGE:
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%
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% INPUTS
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% model COBRA model structure containing the following required fields to perform gDel_minRN.
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% rxns Rxns in the model
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% mets Metabolites in the model
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% genes Genes in the model
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% grRules Gene-protein-reaction relations in the model
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% S Stoichiometric matrix (sparse)
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% b RHS of Sv = b (usually zeros)
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% c Objective coefficients
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% lb Lower bounds for fluxes
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% ub Upper bounds for fluxes
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% rev Reversibility of fluxes
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% function [GR, PR]
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% = GRPRchecker(model, targetMet, givenGvalue)
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%
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% targetMet target metabolites
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% (e.g., 'btn_c')
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% givenGvalue The first column is the list of genes in the original model.
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% The second column contains a 0/1 vector indicating which genes should be deleted.
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% 0 indicates genes to be deleted.
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% 1 indecates genes to be remained.
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% INPUTS:
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% model: COBRA model structure containing the following required fields to perform gDel_minRN.
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%
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% OUTPUTS
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% GR the growth rate obained when the gene deletion strategy is
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% applied and the growth rate is maximized.
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% PR the minimum target metabolite production rate obained
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% when the gene deletion strategy is applied and the growth rate is maximized.
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% *.rxns: Rxns in the model
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% *.mets: Metabolites in the model
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% *.genes: Genes in the model
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% *.grRules: Gene-protein-reaction relations in the model
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% *.S: Stoichiometric matrix (sparse)
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% *.b: RHS of Sv = b (usually zeros)
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% *.c: Objective coefficients
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% *.lb: Lower bounds for fluxes
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% *.ub: Upper bounds for fluxes
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% *.rev: Reversibility of fluxes
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%
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% Feb. 10, 2025 Takeyuki TAMURA
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% targetMet: target metabolites (e.g., 'btn_c')
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% gvalue: The first column is the list of genes in the original model.
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% The second column contains a 0/1 vector indicating which genes should be deleted.
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% 0: indicates genes to be deleted.
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% 1: indecates genes to be remained.
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%
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% OUTPUTS:
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% GR: the growth rate obained when the gene deletion strategy is
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% applied and the growth rate is maximized.
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% PR: the minimum target metabolite production rate obained
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% when the gene deletion strategy is applied and the growth rate is maximized.
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%
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% .. Author: - Takeyuki Tamura, Mar 06, 2025
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%
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@@ -46,7 +48,7 @@
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model2 = model;
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[grRules0] = calculateGR(model, givenGvalue);
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[grRules0] = calculateGR(model, gvalue);
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lb2 = model.lb;
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ub2 = model.ub;
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‎src/design/TrimGdel/README.pdf

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‎src/design/TrimGdel/TrimGdel.m

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function [gvalue, GR, PR, size1, size2, size3, success] = TrimGdel(model, targetMet, maxLoop, PRLB, GRLB)
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%
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% TrimGdel appropriately considers GPR rules and determines
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% a minimal gene deletion strategies to achieve growth-coupled production
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% for a given target metabolite and a genome-scale model.
@@ -8,66 +7,70 @@
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% Gurobi is required for this version.
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% The CPLEX version is available on https://github.com/MetNetComp/TrimGdel
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%
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% function [gvalue, GR, PR, size1, size2, size3, success]
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% = TrimGdel(model, targetMet, maxLoop, PRLB, GRLB)
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% USAGE:
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%
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% function [gvalue, GR, PR, size1, size2, size3, success]
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% = TrimGdel(model, targetMet, maxLoop, PRLB, GRLB)
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%
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% INPUTS:
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% model: COBRA model structure containing the following required fields to perform gDel_minRN.
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%
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% INPUTS
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% model COBRA model structure containing the following required fields to perform gDel_minRN.
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% rxns Rxns in the model
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% mets Metabolites in the model
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% genes Genes in the model
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% grRules Gene-protein-reaction relations in the model
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% S Stoichiometric matrix (sparse)
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% b RHS of Sv = b (usually zeros)
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% c Objective coefficients
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% lb Lower bounds for fluxes
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% ub Upper bounds for fluxes
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% rev Reversibility of fluxes
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% *.rxns: Rxns in the model
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% *.mets: Metabolites in the model
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% *.genes: Genes in the model
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% *.grRules: Gene-protein-reaction relations in the model
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% *.S: Stoichiometric matrix (sparse)
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% *.b: RHS of Sv = b (usually zeros)
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% *.c: Objective coefficients
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% *.lb: Lower bounds for fluxes
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% *.ub: Upper bounds for fluxes
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% *.rev: Reversibility of fluxes
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%
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% targetMet target metabolites
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% (e.g., 'btn_c')
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% maxLoop the maximum number of iterations in gDel_minRN
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% PRLB the minimum required production rates of the target metabolites
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% when gDel-minRN searches the gene deletion
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% strategy candidates.
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% (But it is not ensured to achieve this minimum required value
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% when GR is maximized withoug PRLB.)
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% GRLB the minimum required growth rate
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% when gDel-minRN searches the gene deletion
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% strategy candidates.
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% targetMet: target metabolites (e.g., 'btn_c')
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% maxLoop: the maximum number of iterations in gDel_minRN
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% PRLB: the minimum required production rates of the target metabolites
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% when gDel-minRN searches the gene deletion
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% strategy candidates.
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% (But it is not ensured to achieve this minimum required value
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% when GR is maximized withoug PRLB.)
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% GRLB: the minimum required growth rate
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% when gDel-minRN searches the gene deletion
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% strategy candidates.
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%
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% OUTPUTS
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% gvalue a small gene deletion strategy (obtained by TrimGdel).
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% The first column is the list of genes.
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% The second column is a 0/1 vector indicating which genes should be deleted.
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% 0 indicates genes to be deleted.
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% 1 indecates genes to be remained.
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% GR the maximum growth rate when the obtained gene deletion
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% strategy represented by gvalue is applied.
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% PR the minimum production rate of the target metabolite under
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% the maximization of the growth rate when the obtained gene deletion
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% strategy represented by gvalue is applied.
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% size1 the number of gene deletions after Step1.
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% size2 the number of gene deletions after Step2.
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% size3 the number of gene deletions after Step3.
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% success indicates whether TrimGdel obained an appropriate gene
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% deletion strategy. (1:success, 0:failure)
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% OUTPUTS:
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% gvalue: a small gene deletion strategy (obtained by TrimGdel).
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% The first column is the list of genes.
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% The second column is a 0/1 vector indicating which genes should be deleted.
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% 0: indicates genes to be deleted.
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% 1: indecates genes to be remained.
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% GR: the maximum growth rate when the obtained gene deletion
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% strategy represented by gvalue is applied.
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% PR: the minimum production rate of the target metabolite under
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% the maximization of the growth rate when the obtained gene deletion
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% strategy represented by gvalue is applied.
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% size1: the number of gene deletions after Step1.
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% size2: the number of gene deletions after Step2.
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% size3: the number of gene deletions after Step3.
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% success: indicates whether TrimGdel obained an appropriate gene
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% deletion strategy. (1:success, 0:failure)
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%
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% T. Tamura, "Trimming Gene Deletion Strategies for Growth-Coupled
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% Production in Constraint-Based Metabolic Networks: TrimGdel,"
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% in IEEE/ACM Transactions on Computational Biology and Bioinformatics,
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% vol. 20, no. 2, pp. 1540-1549, 2023.
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% NOTE:
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%
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% Comprehensive computational results are accumulated in MetNetComp
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% database.
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% https://metnetcomp.github.io/database1/indexFiles/index.html
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% T. Tamura, "Trimming Gene Deletion Strategies for Growth-Coupled
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% Production in Constraint-Based Metabolic Networks: TrimGdel,"
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% in IEEE/ACM Transactions on Computational Biology and Bioinformatics,
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% vol. 20, no. 2, pp. 1540-1549, 2023.
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%
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% T. Tamura, "MetNetComp: Database for Minimal and Maximal Gene-Deletion Strategies
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% for Growth-Coupled Production of Genome-Scale Metabolic Networks,"
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% in IEEE/ACM Transactions on Computational Biology and Bioinformatics,
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% vol. 20, no. 6, pp. 3748-3758, 2023,
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% Comprehensive computational results are accumulated in MetNetComp
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% database.
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% https://metnetcomp.github.io/database1/indexFiles/index.html
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%
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% Feb. 10, 2025 Takeyuki TAMURA
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% T. Tamura, "MetNetComp: Database for Minimal and Maximal Gene-Deletion Strategies
69+
% for Growth-Coupled Production of Genome-Scale Metabolic Networks,"
70+
% in IEEE/ACM Transactions on Computational Biology and Bioinformatics,
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% vol. 20, no. 6, pp. 3748-3758, 2023,
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%
73+
% .. Author: - Takeyuki Tamura, Mar 06, 2025
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%
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[gvalue gr pr it success] = gDel_minRN(model, targetMet, maxLoop, PRLB, GRLB) % Step 1

‎src/design/TrimGdel/calculateGR.m

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function [grRules] = calculateGR(model, xname)
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function [grRules] = calculateGR(model, gvalue)
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% calculateGR is a function of gDel_minRN that reads
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% a COBRA model and a 0-1 assignment for genes and outputs whether
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% each reaction is repressed or not.
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%
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% USAGE:
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%
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% function [grRules] = calculateGR(model, gvalue)
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%
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% INPUTS:
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% model: COBRA model structure containing the following required fields to perform gDel_minRN.
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%
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% *.rxns: Rxns in the model
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% *.mets: Metabolites in the model
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% *.genes: Genes in the model
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% *.grRules: Gene-protein-reaction relations in the model
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% *.S: Stoichiometric matrix (sparse)
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% *.b: RHS of Sv = b (usually zeros)
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% *.c: Objective coefficients
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% *.lb: Lower bounds for fluxes
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% *.ub: Upper bounds for fluxes
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% *.rev: Reversibility of fluxes
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%
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% gvalue: The first column is the list of genes in the original model.
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% The second column contains a 0/1 vector indicating which genes should be deleted.
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% 0: indicates genes to be deleted.
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% 1: indecates genes to be remained.
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%
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% OUTPUT:
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% grRules: The first column is the list of GPR-rules. If a reaction does
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% not have a GPR-rule, it is represented as 1.
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% In the second columun, each gene is converted to 0 or 1 based
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% on the given 0-1 assignment, with AND converted to * and OR
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% converted to +.
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% The third comumn contains the calculation results from the
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% second column.
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% The fourth column is 0 if the third column is 0 and 1 if it is
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% greater. If it is 0, the reaction is repressed; if it is 1, it
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% is not repressed.
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%
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% .. Author: - Takeyuki Tamura, Mar 06, 2025
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%
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grRules = cell(size(model.rxns));
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for i=1:size(model.grRules, 1)
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grRules(:, 2) = strrep(grRules, 'or', '+');
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grRules(:,2) = strrep(grRules(:,2), 'and', '*');
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[xname2, index] = sortrows(xname(:,1), 'descend');
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[xname2, index] = sortrows(gvalue(:,1), 'descend');
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for i=1:size(index, 1)
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sorted_gvalue(i, 1) = xname{index(i, 1), 2};
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sorted_gvalue(i, 1) = gvalue{index(i, 1), 2};
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end
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for i = 1:size(model.genes, 1)
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grRules(:, 2) = strrep(grRules(:, 2), xname2{i, 1},num2str(sorted_gvalue(i, 1)));

‎src/design/TrimGdel/e_coli_core.mat

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‎src/design/TrimGdel/example1.m

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function [outputArg1, outputArg2] = example1()
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function [] = example1()
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% example1 calculates the gene deletion strategy for growth coupling
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% for succinate in e_coli_core.
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%
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% Feb. 6, 2025 Takeyuki TAMURA
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% USAGE:
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%
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% function [] = example1()
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%
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% .. Author: - Takeyuki Tamura, Mar 05, 2025
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%
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load('e_coli_core.mat');
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model = e_coli_core;

‎src/design/TrimGdel/example2.m

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function [outputArg1, outputArg2] = example2()
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% example2 calculates the gene deletion strategy for growth coupling
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% for biotin in iML1515.
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%
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% USAGE:
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%
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% Feb. 6, 2025 Takeyuki TAMURA
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% function [] = example2()
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%
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% .. Author: - Takeyuki Tamura, Mar 06, 2025
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%
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load('iML1515.mat');

‎src/design/TrimGdel/example3.m

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function [outputArg1, outputArg2] = example3()
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% example3 calculates the gene deletion strategy for growth coupling
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% for riboflavin in iML1515.
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%
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% USAGE:
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%
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% Feb. 6, 2025 Takeyuki TAMURA
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% function [] = example3()
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%
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% .. Author: - Takeyuki Tamura, Mar 06, 2025
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%
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load('iML1515.mat');

‎src/design/TrimGdel/example4.m

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function [outputArg1, outputArg2] = exampl4()
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% example4 calculates the gene deletion strategy for growth coupling
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% for pantothenate in iML1515.
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%
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% USAGE:
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%
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% Feb. 6, 2025 Takeyuki TAMURA
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% function [] = example4()
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%
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% .. Author: - Takeyuki Tamura, Mar 06, 2025
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load('iML1515.mat');

‎src/design/TrimGdel/example5.m

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function [outputArg1, outputArg2] = example5()
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% example5 calculates the gene deletion strategy for growth coupling
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% for succinate in iMM904.
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%
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% USAGE:
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%
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% Feb. 6, 2025 Takeyuki TAMURA
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% function [] = example5()
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%
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% .. Author: - Takeyuki Tamura, Mar 06, 2025
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%
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load('iMM904.mat');

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