# Exploration¶

biomassPrecursorCheck(model, checkCoupling, checkConservedQuantities, ATN)[source]

Checks if biomass precursors are able to be synthesized.

Usage

[missingMets, presentMets, coupledMets, missingCofs, presentCofs] = biomassPrecursorCheck(model, checkCoupling, checkConservedQuantities)

Input

• model – COBRA model structure

Optional inputs

• checkCoupling – Test, whether some compounds can only be produced if there is a sink for other biomass precursors (Default: false)
• checkConservedQuantities – true to check whether the cofactor pairs containing conserved moieties (defined by the network structure) can be synthesized (e.g., ATP, NAD, NADPH, ACCOA, AA-charged tRNA, fatty acyl-ACP). They will otherwise be identified as missingMets (Default: false)
• ATN – atom transition network outputed by buildAtomTransitionNetwork If provided, true internal conserved moieties will be identified and used for checking conserved quantities (default [])

Outputs

• missingMets – List of biomass precursors that are not able to be synthesized
• presentMets – List of biomass precursors that are able to be synthesized
• coupledMets – List of metabolites which need an exchange reaction for at least one other biomass component because their production is coupled to it (returned only if checkCoupling = true)
• missingCofs – List of cofactor pairs (defined by the network conserved moieties) that are not able to be synthesized (returned only if checkConservedQuantities = true)
• presentCofs – List of cofactor pairs that are able to be synthesized (returned only if checkConservedQuantities = true)
essentialRxn4MultipleModels(allModels, objFun)[source]

Performs single reactions deletions across multiple models and identifies which reactions have variable essentiality across all models for the chosen objective function (eg. it identifies reactions whos deletion would result in a zero flux through ATP consumption reaction - ATPM).

Usage

[essentialRxn4Models, dataStruct] = essentialRxn4MultipleModels(allModels, objFun)

Inputs

• allModels – directory of the structure with multiple COBRA model structures
• objFun – string with objective function reaction (e.g. ‘ATPM’)

Outputs

• essentialRxn4Models – Table with reaction fluxes (within the objective function reaction) after single deletion of model reaction (rows) across models (columns)
• dataStruct – Structure with all models

Example

[essentialRxn4Models, dataStruct] = essentialRxn4MultipleModels(allModels, 'ATPM')

findBlockedReaction(model, method)[source]

Determines those reactions which cannot carry any flux in the given simulation conditions.

Usage

BlockedReaction = findBlockedReaction(model)

Input

• model – COBRA model structure

Optional input

• method – ‘FVA’ for flux variability analysis (default) ‘L2’ for 2-norm minimization

Output

• blockedReactions – List of blocked reactions
findCarbonRxns(model, nCarbonThr)[source]

Returns the list of reactions that act of compounds which contain cabons greater than the thershhold set.

Usage

[hiCarbonRxns, zeroCarbonRxns, nCarbon] = findCarbonRxns(model, nCarbonThr)

Inputs

• model – Structure containing all necessary variables to described a stoichiometric model
• nCarbonThr – defines the min # of carbons that a metabolite, that is acted on in a reaction, can have in the final list of reactions

Outputs

• hiCarbonRxns – The list of reactions that act on metabolites with greater than the threshold number of carbons
• zeroCarbonRxns – Reactions with no carbon
• nCarbon – The number of carbons in each metabolite in the model
findEpistaticInteractions(model, doubleDeletionFitness, lethalFlag, minEffect)[source]

Finds synthetic lethal and/or synthetic sick interactions based on double deletion analysis data

Usage

[interactions, epistaticEffect] = findEpistaticInteractions(model, doubleDeletionFitness, lethalFlag, minEffect)

Inputs

• model – COBRA model structure
• doubleDeletionFitness – A matrix of fitness (or growth rate) values for each of the double deletion strains. The diagonal of this matrix contains the single deletion fitness values.

Optional inputs

• lethalFlag – Only consider SL interactions (Default = false)
• minEffect – Minimum fitness effect considered to be significant (Default = 1e-2)

Outputs

• interactions – A sparse binary matrix indicating a SL or SS interaction between two genes in the model
• epistaticEffect – Magnitude of the epistatic interaction defined as min(f1-f12, f2-f12) where f1 and f2 are the fitness values for the deletion strain of gene 1 and gene 2 respectively and f12 is the fitness value for the double deletion strain of genes 1 and 2

Note

The criteria for establishing a synthetic sick interaction are that the double deletion strain fitness must be at least minEffect lower than the fitness of either of the single deletion strains, i.e. f12 < f1 - minEffect and f12 < f2 - minEffect

The additional criterion for establishing a synthetic lethal interaction is that the double deletion fitness value is smaller than minEffect (i.e. essentially zero) f12 < minEffect

Note that the interactions matrix double counts all interactions

findExcRxns(model, inclObjFlag, irrevFlag)[source]

Finds exchange and uptake rxns

Usage

[selExc, selUpt] = findExcRxns(model, inclObjFlag, irrevFlag)

Input

• model – COBRA model structure

Optional inputs

• inclObjFlag – Include objective rxns in the exchange rxn set (1) or not (0) (Default = false)
• irrevFlag – Model is in irreversible format (1) or not (Default = false)

Outputs

• selExc – Boolean vector indicating whether each reaction in model is exchange or not
• selUpt – Boolean vector indicating whether each reaction in model is nutrient uptake or not

Note

Exchange reactions only have one non-zero (+1 / -1) element in the corresponding column of the stoichiometric matrix. Uptake reactions are exchange reactions are exchange reactions with negative lower bounds.

findGPRFromRxns(model, rxnIDs)[source]

Get the Textual representations of the GPR rules for the indicated reactions. Usage

gprs = findGPRFromRxns(model,rxnIDs)

Inputs

• model – The model to retrieve the GPR rules from
• rxnIDs – The reaction IDs to obtain the GPR rules for

Output

• gprs – The textual GPR Rules

Authors:

Thomas Pfau Dec 2017
findGeneIDs(model, geneList)[source]

Finds gene numbers in a model

Usage

geneID = findGeneIDs(model, geneList)

Inputs

• model – COBRA model structure
• geneList – List of genes

Output

• geneID – List of gene IDs corresponding to geneList
findGenesFromRxns(model, reactions)[source]

Make a gene list of the genes that correspond to the selected reactions

Usage

[geneList] = findGenesFromRxns(model, reactions)

Inputs

• model – COBRA model structure
• reactions – Reactions to find the corresponding genes for

Output

• geneList – List of genes corresponding to reactions
findHiCarbonRxns(model, nCarbonThr)[source]

Returns the list of reactions that act on compounds which contain cabons greater than the threshold set.

Usage

[hiCarbonRxns, nCarbon] = findHiCarbonRxns(model, nCarbonThr)

Inputs

• model – Structure containing all necessary variables to describe a stoichiometric model
• nCarbonThr – defines the min # of carbons that a metabolite, that is acted on in a reaction, can have in the final list of reactions

Outputs

• hiCarbonRxns – The list of reactions that act on metabolites with greater than the threshold number of carbons
• zeroCarbonRxns – Reactions with no carbon
• nCarbon – The number of carbons in each metabolite in the model
findMatchingFieldEntries(field, searchString, isAnnotation, minSim)[source]

Find elements of the field that are similar to the provided identifier

Usage

[matchingIDs, positons, similarities] = findMatchingFieldEntries(field, searchString, isAnnotation, minSim)

Inputs

• field – A Cell Array of strings
• searchString – The item to search for
• isAnnotation – Whether the strings in the field are annotation strings (multiple identifiers are concatenated with ; and will be separated)
• minSim – minimum “similarity” between element and search item.

Outputs

• matchingIDs – All IDs which are matching to the search string.
• positions – The positions of these IDs in the supplied field.
• similarities – Similarities of the matchingIDs with the search String
findMetFromCompartment(model, compartment)[source]

Finds all the metabolites and their identifiers in a compartment of interest.

Usage

[compartmentMetabolites] = findMetFromCompartment(model,Compartment)

Inputs

• model – COBRA model strcture
• compartment – compartment of interest (e.g.: ‘[m]’, ‘[n]’, ‘[e]’, etc.)

Output

• compartmentMetabolites – List of metabolites in the compartment of interest
findMetIDs(model, metList)[source]

Finds metabolite numbers in a model

Usage

metID = findMetIds(model, metList)

Inputs

• model – COBRA model structure
• metList – List of metabolites

Output

• metID – List of metabolite IDs corresponding to metList
findMetabolicJunctions(model, nRxnsJnc)[source]

Finds metabolic branchpoints with different numbers of branches

Usage

validJunctionMets = findMetabolicJunctions(model, nRxnsJnc)

Inputs

• model – COBRA model structure
• nRxnJnc – Number of reactions to be considered a junction

Output

• validJunctionMets – List of junction metabolites
findMetsFromRxns(model, reactions)[source]

Get all Metabolites from a set of reactions.

Usage

[metList, stoichiometries] = findMetsFromRxns(model, reactions) [metList] = findMetsFromRxns(model, reactions)

Inputs

• model – COBRA model structure
• reactions – Reaction IDs (Cell Array) or positions (Double array) to find the corresponding metabolites for

Outputs

• metList – If only one output is requested, returns an ordered set of all metabolites involved in the provided reactions. Otherwise, this is a Cell Array of cell arrays containing the metabolites involved in each of the provided reactions.
• stoichiometries – this is a Cell array of double arrays of the stoichiometric coefficients corresponding to the reactions in the order of provided reaction ids. If reactions not in the model are provided, those will be represented by empty arrays.
findNeighborRxns(model, rxns, asSingleArray, order, commonMets, withComp)[source]

Identifies the reactions and the corresponding genes that are adjacent (having a common metabolite) to a reaction of interest. Useful for characterizing the network around an orphan reaction.

Usage

[neighborRxns, neighborGenes, mets] = findNeighborRxns(model, rxns, asSingleArray, order, commonMets, withComp)

Inputs

• model – COBRA model structure
• rxns – the target reaction as a string or multiple reactions as cell array

Optional inputs

• asSingleArray – If false, then return cell array of cell arrays with neighbor reactions for one particular connecting metabolite and input reaction combination. Else just return all neighbors in one cell array. (Default = false)
• order – maximal order of neighbors to be returned (default = 1) order >= 2 only works with asSingleArray = true Neighborhoods of order >= 2 will usually also return the input reactions.
• commonMets – Cell array of common metabolites, that should not count as edges between reactions. Use {‘’} if no such metabolite should be included (default = {‘atp’, ‘adp’, ‘h’, ‘h2o’, ‘pi’, ‘ppi’}).
• withComp – if commonMets already have a compartment identifier, e.g. ‘atp[m]’, then true (default=false)

Outputs

• neighborRxns – the neighboring rxns in the network, (having common metabolites)
• neighborGenes – the genes associated with the neighbor rxns
• mets – the metabolites in the target reaction
findOrphanRxns(model)[source]

Finds all orphan reactions in model (reactions with no associated genes), not including exchange rxns

Usage

orphans = findOrphanRxns(model)

Input

• model – a COBRA model with GPRs

Output

• orphans – all orphan reactions in the model
findRootNPmets(model, findNCmets)[source]

Finds the root no production (and no consumption) metabolites in a model, used by gapFind

Usage

gaps = findRootNPmets(model, findNCmets)

Input

• model a COBRA model

Optional input

• findNCmets – find no consumption mets as well as no production (default = false)

Output

• gaps – all root no production metabolites
findRxnFromCompartment(model, compartment)[source]

Finds all the reactions and their identifiers in a compartment of interest.

Usage

[compartmentReactions] = findRxnFromCompartment(model,Compartment)

Inputs

• model – COBRA model strcture
• compartment – compartment of interest (e.g.: ‘[m]’, ‘[n]’, ‘[e]’, etc.)

Output

• compartmentMetabolites – List of reactions in the compartment of interest
findRxnIDs(model, rxnList)[source]

Finds reaction numbers in a model

Usage

rxnID = findRxnIDs(model, rxnList)

Inputs

• model – COBRA model strcture
• rxnList – List of reactions

Output

• rxnID – IDs for reactions corresponding to rxnList
findRxnsActiveWithGenes(model, genes)[source]

Finds all reactions for which the provided genes show sufficient evidence (i.e. are usfficient according to the GPRs)

Usage

[Reaclist] = findRxnsActiveWithGenes(model, genes)

Inputs

• model – COBRA model structure
• genes – A list of gene identifiers

Output

• Reaclist – Cell array of reactions which are supported by the provided genes

Note

Only reactions which do have a GPR are considered for this function. Reactions without GPRs are ignored, as we don’t have evidence.

findRxnsFromGenes(model, genes, numericFlag, ListResultsFlag)[source]

Print every reaction associated with a gene of interest

Usage

[results, ListResults] = findRxnsFromGenes(model, genes, numericFlag, ListResultsFlag)

Inputs

• model – COBRA model structure
• genes – string of single gene or cell array of multiple genes for which rxns are desired.

Optional inputs

• numericFlag – 1 if using Human Recon (Default = 0)
• ListResultsFlag – 1 if you want to output ListResults (Default = 0)

Outputs

• results – structure containing cell arrays for each gene. Each cell array has one column of rxn abbreviations and one column containing the reaction formula
• ListResults – same as above, but in a cell array
findRxnsFromMets(model, metList, varargin)[source]

Returns a list of reactions in which at least one metabolite listed in metList participates.

Usage

[rxnList, rxnFormulaList] = findRxnsFromMets(model, metList, printFlag)

Inputs

• model – COBRA model structure
• metList – Metabolite list

Optional inputs

• printFlag – Print reaction formulas to screen (Default = false)
• Property/Value – Allowed Properties are: * containsAll - If true only reactions containing all metabolites in metList are returned (Default: false) * printFlag - as above, will overwrite a printFlag set individually (Default: false) * producersOnly - Only return reactions which produce any of the given metabolites. (Default: false) * consumersOnly - Only return reactions which consume any of the given metabolites. (Default: false) * exclusive - Only return those reactions, which do not contain any metabolites but those given (Default: false)

Outputs

• rxnList – List of reactions
• rxnFormulaList – Reaction formulas coresponding to rxnList
findRxnsFromSubSystem(model, subSystem)[source]

Find all reactions which are part of a given subsystem.

Usage

[reactionNames,rxnPos] = findRxnsFromSubSystem(model,subSystem)

Inputs

• model – A COBRA model struct with at least rxns and subSystems fields
• subSystem – A String identifying a subsystem

Outputs

• reactionNames – A Cell array of reaction names
• rxnPos – A double array of positions of the reactions in reactionNames in the model (same order).

Usage

%Obtain all reactions with Glycolysis in their respective subSystems
field.

[reactionNames,rxnPos] = findRxnsFromSubSystem(model,’Glycolysis’)

findRxnsInActiveWithGenes(model, genes)[source]

Finds all reactions for which the provided genes show sufficient evidence of their absence. (i.e. make the corresponding GPRs always be zero)

Usage

[Reaclist] = findRxnsActiveWithGenes(model, genes)

Inputs

• model – COBRA model structure
• genes – A list of gene identifiers

Output

• Reaclist – Cell array of reactions which are supported by the provided genes

Note

Only reactions which do have a GPR are considered for this function. Reactions without GPRs are ignored, as we don’t have evidence.

findSubSysGen(model)[source]

Lists the subsystem that a reaction occurs in encoded by a gene. Returns list of subsystems. If multiple reactions are associated with gene, subsystem of first occurance will be listed.

Usage

[GenSubSystem] = findSubSysGen(model)

Input

• model – COBRA model structure

Output

• GenSubSystem – array listing genes and subsystmes
findSubSystemsFromGenes(model, genes, varargin)[source]

Returns the subsystems associated with the provided genes.

Usage

[geneSubSystems,singleList] = findSubSystemsFromGenes(model,genes,...)

Input

• model – COBRA model structure

Optional inputs

• genes – The genes to find subSystems for (Default: model.genes)
• varargin – Optional arguments as parameter/value pairs, or parameter struct. * structResult - return individual Gene Associations as a struct instead of a Cell Array with each gene represented by a field. Gene names might be adapted to fit to field names and all genes will be prefixed with gene_. * onlyOneSub - Only return one subSystem for each gene.

Output

• geneSubSystems – All subsystems associated with the provided genes.

Optional output

• singleList – A Cell array of size(nGenes,2), with the first column representing the gene and the second column containing the subSystems associated with the gene.
findTrspRxnFromMet(model, metList, compFlag)[source]

Find transport reactions for defined metabolites. Option available to define the compartment of the transport

Usage

[TrspRxns] = findTrspRxnFromMet(model, metList, compFlag)

Inputs

• model – COBRA model structure
• metList – metabolites list

Optional input

• compFlag – compartment of the transport (e.g. ‘c’, cytosol)

Output

• TrspRxns – List of transporters reactions
getMIRIAMAnnotations(model, type, varargin)[source]

Get the MIRIAM Annotations a struct array of annotation structs for the given type

Usage

annotations = getMIRIAMAnnotations(model,field,...)

Inputs

• model – The COBRA model structure.
• type – the basic field to get annotations for (e.g. rxn, met, or model

Optional input

• varagin – Additional arguments as parameter/value pairs. * bioQualifiers - A Cell array of BioQualifiers to look for if not provided, or empty, all bioQualifiers defined in getBioQualifiers() will be used * ids - A specific ID or IDs to get the annotation data for. Cannot be combined with type model.(Default: model.([type ‘s’])).

Output

• annotations – A struct array with the following structure: * .annotation -> A Struct array with one element per element of the given type. * .annotation.cvterms -> A Struct array of controlled vocabulary terms with one element per qualifier used * .annotation.cvterms.qualifier -> the bioQualifier for this all ressourcesof this cvterm * .annotation.cvterms.qualifierType -> the Qualifier type (modelQualifier or bioQualifier) for all ressources of this cvterm * .annotation.cvterms.ressources -> struct with the following fields: * .annotation.cvterms.ressources.database -> the database for this ressource. * .annotation.cvterms.ressources.id-> The ID in the database for this ressource.
getModelSizes(model)[source]

Get the sizes of the basic fields of the model structure

Usage

[nMets, nRxns, nCtrs, nVars, nGenes, nComps] = getModelSizes(model)

Input

• model – A COBRA model structure

Outputs

• nMets – The number of metabolites in the model
• nRxns – The number of reactions in the model
• nCtrs – The number of constraints in the model
• nVars – The number of variables in the model
• nGenes – The number of genes in the model
• nComps – The number of compartments in the model
getModelSubSystems(model)[source]

Get all subSystems present in a model

Usage

[subSystems] = getModelSubSystems(model)

Input

• model – A COBRA model struct with at least the subSystems fields

Output

• subSystems – A Cell Array of strings containing all subSystems in the model

Usage

%Get all subSystems present in the model. [subSystems] = getModelSubSystems(model)
getObjectiveSense(model)[source]

Get the objective sense of the model (both the osenseStr (‘max’ or ‘min’) and the correspdoning osense value (-1 or 1)

Usage

[osenseStr,osense] = getObjectiveSense(model)

Input

• model – The model to obtain the sense for. If the model has a osenseStr field, it has to be either ‘min’ or ‘max’ (case insensitive) otherwise this function will error.
OUTPUS:
osenseStr: ‘min’ or ‘max’ osense: 1 or -1;
identifyFastBlockedRxns(model, rxnList, printLevel)[source]

This function evaluates the presence of blocked reactions in a metabolic model

Usage

[BlockedRxns] = identifyFastBlockedRxns(model,rxnList)

Inputs

• organisms – model in COBRA model structure format
• rxnList – nx1 cell array with reactions to test
• printLevel – Verbose level (default: printLevel = 1)

Output

• BlockedRxns – nx1 cell array containing blocked reactions
isReactionInSubSystem(model, reactions, subSystem)[source]

Determine whether a reaction is in a given subSystem.

Usage

[subSystems] = getModelSubSystems(model)

Inputs

• model – A COBRA model struct with at least rxns and subSystems fields
• reactions – Either a string identifying a reaction, or a cell array of strings identifying multiple reactions, or a double vector identifying the positions.
• subSystem – A String identifying a subsystem.

Output

• present – a boolean vector for each provided reaction.

Usage

%Get all subSystems present in the model. [subSystems] = getModelSubSystems(model)
plotEssentialRxns(essentialRxn4Models, essentialityRange, numModelsPresent)[source]

Identifies and plots (heatmap) a set of essential reactions (reactions of interest) based on conditional inputs.

Usage

rxnInterest4Models = plotEssentialRxns(essentialRxn4Models, essentialityRange, numModelsPresent)

Inputs

• essentialRxn4Models – Table with reaction fluxes (within the objective function reaction) after single deletion of model reaction (rows) across models (columns) This input can be obtained from essentialRxn4MultipleModels.m
• essentialityRange – Range of fluxes (e.g. [-100,100])
• numModelsPresent – Minimum number of models where a reaction is essential in order to be ploted.

Output

• rxnInterest4Models – Table with reaction fluxes (within the objective function reaction) for reactions of interest (rows) across models (columns)

Example

rxnInterest4Models = plotEssentialRxns(essentialRxn4Models, essentialityRange, numModelsPresent)

printConstraints(model, minInf, maxInf)[source]

Print all network constraints that are not -Inf (minInf) or +Inf (maxInf)

Usage

printConstraints(model, minInf, maxInf)

Inputs

• model – COBRA model structure
• minInf – value that is considered as -Inf (or desired minimum cutoff value)
• maxInf – value that is considered as +Inf (or desired maximum cutoff value)
printFluxBounds(model, rxns)[source]

Prints the reactionID and upper/lower flux bounds.

Usage

printFluxBounds(model, rxns)

Input

• model – The model to print

Optional input

• rxns – a string array of reaction ids for which flux bounds need to be printed
printFluxVector(model, fluxData, nonZeroFlag, excFlag, sortCol, fileName, headerRow, formulaFlag)[source]

Prints a flux vector with reaction labels

Usage

printFluxVector(model, fluxData, nonZeroFlag, excFlag, sortCol, fileName, headerRow, formulaFlag)

Inputs

• model – COBRA model structure
• fluxData – Data matrix/vector (for example, solution.x)

Optional inputs

• nonZeroFlag – Only print nonzero rows (Default = false)
• excFlag – Only print exchange fluxes (Default = false)
• sortCol – Column used for sorting (-1, none; 0, labels; >0, data columns;) (Default = -1)
• fileName – Name of output file (Default = [])
• headerRow – Header (Default = [])
• formulaFlag – Print reaction formulas (Default = false)
printGPRForRxns(model, rxnIDs, printLevel)[source]

Print the GPRs (in textual format) for the given RxnIDs Usage

gprs = printGPRForRxns(model,rxnID)

Inputs

• model – The model to retrieve the GPR rules from
• rxnIDs – The reaction IDs to obtain the GPR rules for

Optional input

• printLevel – Whether to print out the GPRs. If printLevel is 0, the function will only return the Strings in a cell array.

Output

• gprs – The textual GPR Rules

Authors:

Thomas Pfau Dec 2017
printLabeledData(labels, data, nonzeroFlag, sortCol, fileName, headerRow, sortMode)[source]

Print a matrix of data with labels

Usage

printLabeledData(labels, data, nonzeroFlag, sortCol, fileName, headerRow, sortMode)

Inputs

• labels – Row labels
• data – Data matrix/vector
• nonzeroFlag – Only print nonzero rows (opt)
• sortCol – Column used for sorting (-1, none; 0, labels; >0, data columns; opt)
• fileName – Name of output file (opt)
• sortMode – Sort mode, ‘ascend’ or ‘descend’ (opt, default ‘ascend’)
printMatrix(A, format, file)[source]

Prints matrix into a file or screen

Usage

printMatrix(A, format, file)

Inputs

• A – Matrix
• format – Format string (opt, default ‘%6.4ft’)
• file – File name (opt)
printRxnFormula(model, varargin)[source]

Prints the reaction formulas for a list of reactions

Reactions that have an upperbound <= 0 and lowerbound < 0 will have its directionality reversed unless directionFlag = false.

Usage

formulas = printRxnFormula(model, varargin)

Input

• model – COBRA model structure

Optional input

• varargin – Optional Inputs provided as ‘ParameterName’, Value

pairs. the following parameternames are available:

• rxnAbbrList: Cell array of rxnIDs to be printed (Default = print all reactions)
• printFlag: Print formulas or just return them (Default = true)
• lineChangeFlag: Append a line change at the end of each line
(Default = true)
• metNameFlag: Print full met names instead of abbreviations
(Default = false)
• fid: Optional file identifier for printing in files
(default 1, i.e. stdout)
• directionFlag: Checks directionality of reaction. See Note.
(Default = false)
• gprFlag: Print gene protein reaction association
(Default = false)
• proteinFlag: Print the protein names associated with the genes in the
GPRs associated with the reactions. (Default = false)
• printBounds: Print the upper and lower Bounds of the reaction (Default = false)

Output

• formulas – Cell array containing formulas of specified reactions

Example

1) print only ATPM and TKT1:
printRxnFormula(model,'rxnAbbrList',{'ATPM','TKT1'});
2) print the reactions of the model with the metabolite Names instead of ids.
printRxnFormula(model, 'metNameFlag',true);
3) print all reactions with the metabolite names to a given fileID
printRxnFormula(model, 'metNameFlag',true, 'fid', fileID);

printUptakeBound(model)[source]

Returns the indices to the substrate uptake reactions and prints substrate uptake bounds

Usage

uptakeInd = printUptakeBound(model)

Input

• model – CORBRA model structure

Output

• upInd – Vector containing indecies of uptake reactions
searchModel(model, searchTerm, varargin)[source]

Search for the specified term in the given model. The performed search is fuzzy if similarity is lower than 1.

Usage

results = searchModel(model,searchTerm,...)

Inputs

• model – The model to search in

• searchTerm – The term to search for

• varargin – Additional parameters as parameter/value pairs or value struct. Available parameters are:

• printLevel - Printout switch, 0 silent, 1 print results. (Default = 1) .
• similarity - Minimum similarity (as provided in calcSim) for matches.

Output

• results – The results struct build as follows:
• .field - a struct array containing of the basic fields (e.g. rxns, mets etc) of the model in which matches were found with each field indicating the matches as detailed below.
• .field.id - The id of the matching element
• .field.matches - information about the matches of the respective ID.
• .field.matches.value - the value that matched.
• .field.matches.source - the field that contained the matching value.
surfNet(model, metrxn, metNameFlag, flux, nonzeroFluxFlag, showMets, field2print, nCharBreak, iterOptions)[source]

A simple and convenient tool to navigate through the metabolic network interactively, possibly with given flux vectors, in the Matlab command window using mouse once the starting point is called by command.

Usage

surfNet(model, metrxn, metNameFlag, flux, NonzeroFluxFlag, showMets,field2print, nCharBreak)

Input

• model – COBRA model

Optional inputs

• metrxn – mets or rxns names, can be a cell array of multiple rxns and mets, or simply a string (default: objective reactions or a random reaction)
• metNameFlag – print model.metNames in reaction formulas. (default: false)
• flux – flux vectors for the model, a #reactions x #columns matrix. (default: []) If given, the producing and consuming reactions displayed are in accordance with the flux direction.
• nonzeroFluxFlag – show only reactions with nonzero fluxes if flux is given (default: true)
• showMets – show metabolites in a list when printing reactions (default: true)
• field2print – print fields associated with mets or rxns, e.g. metNames, rxnNames, grRules. Either: (i) a cell array of two cells, 1st being a character array for met fields and 2nd for rxn fields or (ii) a character array of field names recognizable from the field names or the sizes (default: {{‘metNames’,’metFormulas’}, {‘rxnNames’,’lb’,’ub’}})
• nCharBreak – max. no. of characters per line for reaction formulas (default 0, the current width of the command window)

Example

surfNet(model, 'glc-D[c]')  % for starting the navigation at D-glucose
surfNet(model, 'EX_glc-D(e)')  % for starting the navigation at the glucose exchange reaction
surfNet(model, 'glc-D[c]', 1)  % for printing model.metNames in reaction formulas
surfNet(model, 'glc-D[c]', 0, flux, 1)  % for starting at glucose and show reactions with non-zero flux in 'flux' only
surfNet(model, 'EX_glc-D(e)', 0, [], [], 0)  % to show the reaction formulas only but not the details of metabolites during navigation
surfNet(model, {'glc-D[c]'; 'fru[c]'})  % to view several mets and rxns