Utilities

buildRxnGeneMat(model)

Build the rxnGeneMat based on the given models rules field

USAGE:

model = buildRxnGeneMat(model)

INPUT:

model: Model to build the rxnGeneMat. Must have the rules field,

otherwise the rxnGeneMat is empty

OUTPUT:

model: The Model including a rxnGeneMat field.

convertOldCouplingFormat(model, printLevel)

Converts an old style model implementation of coupling constraints to a new style

INPUT:

model: model with model.A but without model.d

OPTIONAL INPUT:

printLevel: The verbosity level (0 (default) no messages >=1 warnings)

OUTPUT:

model: A COBRA model structure with the following fields

• .S - The stoichiometric matrix

• .c - Objective coeff vector

• .lb - Lower bound vector

• .ub - Upper bound vector * .b: accumulation/depletion vector (default 0 for each metabolite). * .C: the Constraint matrix; * .d: the right hand side vector for C; * .dsense: the constraint sense vector;

convertOldStyleModel(model, printLevel, convertOldCoupling)

Converts several old fields to their replacement.

USAGE:

model = convertOldStyleModel(model) model = convertOldStyleModel(model, printLevel)

INPUT:

model: a COBRA Model (potentially with old field names)

OPTIONAL INPUT:

printLevel: boolean to indicate whether warnings and messages are given (default, 1). convertOldCoupling boolean to indicate whether to convert model.A

into model.S and model.C, etc.

OUTPUT:

model: a COBRA model with old field names replaced by new ones and

duplicated fields merged.

Note

There are multiple fields which were used inconsistently in the course of the COBRA toolbox. This function provides a simple way to get these model fields converted to the current names. In addition, some fields were commonly not present in older models and are now checked in many newer models. These fields are initialized by this function, with default values, which do not alter any previous behaviour. The model fields changed are as follows: ‘confidenceScores’ -> ‘rxnConfidenceScores’ ‘metCharge’ -> ‘metCharges’ ‘ecNumbers’ -> ‘rxnECNumbers’ ‘KEGGID’ -> ‘metKEGGID’ ‘metKeggID’ -> ‘metKEGGID’ ‘rxnKeggID’ -> ‘rxnKEGGID’ ‘metInchiString’ -> ‘metInChIString’ ‘metSmile’ -> ‘metSmiles’ ‘metHMDB’ -> ‘metHMDBID’ If both an old and a new field is present, data from old fields is merged into new fields, with the data of new fields taking precedence (i.e. if not data is present in the new field at any position, the old field data replaces it, otherwise the new field data is kept. Furthermore, fields deemed to be required for Flux Balance analysis are generated if not present: osenseStr: Objective Sense.

By default this field is initialized as ‘max’. If osense is present, a -1 will be translates as ‘max’ and a 1 will be translated as ‘min’

csense: Constraint sense.

This field indicates the sense of the b matrix, i.e. if b stands for lower than (‘L’) or greater than (‘G’) or equality constraints (‘E’). It is initialized as a char vector of ‘E’ with the same size as model.mets.

genes: A Field for genes present in the model. rules: The rules field is a logical representation of the GPR rules,

and used in multiple functions. If the grRules field is present, this field will be initialized according to grRules, otherwise it will be initialized as a cell array of the ame size as model.rxns with empty strings in each cell.

rev: This field was deprecated and is therefore removed, for

reversibility determination the toolbox relies on the lower bounds of the reactions.

The following fields might be altered to adhere to the definitions in the COBRAModelFields documentation: rxnConfidenceScores: This field is defined as a number betwen 0 and 4

indicating the confidence of a reaction. It is therefore assumed to be a double vector in COBRA functions. Some old models provide this as Strings, or a numeric cell array. Those fields are converted to double vectors, with the data retained.

Fields with Cell arrays: Some older models have defined cell array fields

which have individual cells which are numeric (i.e. empty []). These empty cells are replaced by ‘’ for those fields, which are defined in the COBRAModelFields file as having cell arrays with chars.

createEmptyFields(model, fieldNames, fieldDefinitions)

Create the specified model field with its default values. Works only for fields defined in the toolbox if fieldDefinitions are not supplied.

USAGE:

model = createEmptyFields(model,fieldName, fieldDefinitions)

INPUTS:

model: The model to add a field to fieldNames: The names of the fields to add.

OPTIONAL INPUTS:

fieldDefinitions: The Specifications of the field. Only necessary

if a field which is not defined yet should be added.

OUTPUTS:

model: The original model struct with the specified

field added.

Author:

Thomas Pfau Nov 2017

creategrRulesField(model, positions)

Generates the grRules optional model field from the required rules and gene fields.

USAGE:

modelWithField = creategrRulesField(model, positions)

INPUT:

model: The COBRA Model structure to generate the grRules Field for

an existing grRules field will be overwritten

OPTIONAL INPUT:

positions: The positions to update. Can be supplied either as

logical array, double indices, or reaction names (Default: model.rxns) If the model did not have grRules before, ALL rxns will have grRules created

OUTPUT:

model: The Output model with a grRules field

generateFieldDescriptionFile(FileName)

Generates the ModelFields.md file describing the Required and Optional Fields of a COBRA model.

USAGE:

FileString = generateFieldDescriptionFile(FileName)

OPTIONAL INPUT:

FileName: The FileName to write to. (default [CBTDIR filesep ‘docs’ filesep ‘notes’ filesep ‘COBRAModelFields.md’])

OUTPUT:

FileString: The string written to the specified filename (or the default file)

getDatabaseMappings(field, qualifiers)

getDataBaseMappings returns information on known mappings of database entries to model field names, along with additional information about the fields.

INPUT:

field: the basic model field to extract mappings for (e.g. ‘met’, ‘gene’, ‘rxn’)

OPTIONAL INPUT:

qualifiers: the qualifiers to restrict the selection to.

These have to be part of the bioql modifiers definition (e.g. is, isDescribedBy, isEncodedBy etc) providing ‘all’ will return all associated Database mappings. Default: ‘all’

OUTPUT:

returnedmappings: The mappings known for the given field. The

structure is: X{:,1} : the database ID (in identifiers.org/miriam annotation) X{:,2} : The qualifier associated with the DB X{:,3} : The model field associated with this db X{:,4} : The association field (met/rxn/gene/prot/comp) X{:,5} : The specified regular expression the identifier has to adhere to. X{:,6} : The type of the qualifier (modelQualifier or bioQualifier)

getDefaultCompartmentSymbols()

Returns the default compartment symbol and name lists to use for model IO or compartment matching USAGE:

[defaultCompartmentSymbolList, defaultCompartmentNameList] = getDefaultCompartmentSymbols()

OUTPUT:

defaultCompartmentSymbolList: a List of abbreviations of

compartment names

defaultCompartmentNameList: a List of names of compartments where element i corresponds

to the i-th abbreviation in defaultCompartmentSymbolList

getDefaultCompartments()

GETDEFAULTCOMPARTMENTS returns the default compartment Symbols and default Compartments

USAGE: [ compSymbolList, compNameList ] = getDefaultCompartments( )

OUTPUT:

compSymbolList: Default symbols of compartments compNameList: Names of the default compartments.

getDefinedFieldProperties(varargin)

Returns the fields defined in the COBRA Toolbox along with checks for their properties

A list of fields of a COBRA structure is described in https://github.com/opencobra/cobratoolbox/blob/master/docs/source/notes/COBRAModelFields.md and defined computationally in: src/base/io/definitions/COBRA_structure_fields.tab

USAGE:

[fields] = getDefinedFieldProperties(varargin)

OPTIONAL INPUT:

varargin: The following parameter/value pairs can be used:

• Descriptions: Whether to obtain the field descriptions (default = false).

• SpecificFields: Indication whether to only obtain definitions for a specific set of fields (default all).

• DataBaseFields: Get the fields with specified Database relations (true, if requested).

OUTPUTS:

fields: All fields and their properties as requested, if

fields without definitions are requested, they will not be contained in the result.

Note

The optional inputs are to be provided as parameter/value pairs. The returned Cell arrays are structured as follows: Default:

• X{:,1} are the field names

• X{:,2} are the associated fields for the first dimension (i.e. size(model.(X{A,1}),1) == size(model.(X{A,2}),1) has to evaluate to true

• X{:,3} are the associated fields for the second dimension (i.e. size(model.(X{A,1}),2) == size(model.(X{A,2}),1) has to evaluate to true

• X{:,4} are evaluateable statements, which have to evaluate to true for the model to be valid, these mainly check the content types.

• X{:,5} are default values (or evaluateable strings for cell arrays)

E.g.

x = model.(X{A, 1});

eval(X{A, 4}) has to return 1

DataBaseFields:

• X{:, 1} - database id

• X{:, 2} - qualifier

• X{:, 3} - model Field

• X{:, 4} - model field reference (without s)

• X{:, 5} - Patterns for ids from the respecive database.

getDistributedModel(modelName, description)

Loads the indicated model from the models submodule.

USAGE:

model = getDistributedModel(modelName)

INPUT:

modelName: The name of the model including the file extension

OPTIONAL INPUTS:

description: If the model description should be set to a

specific value

OUTPUTS:

model: The loaded model from the models submodule (i.e.

those distributed for the test suite)

getDistributedModelFolder(modelName)

Identifies the folder a distributed model is located in. This function only works with models distributed for testing here: cobratoolbox/test/models

USAGE:

modelDir = getDistributedModelFolder(modelName)

INPUT:

modelName: The name of the model including the file extension

OUTPUTS:

modelDir: The folder the model should be located in.

getMultiDimensionFields(fieldDefinitions)

Get those fields which have multiple dimensions depending on another field from the definitions

USAGE:

[fieldNames,firstDim,secondDim] = getMultiDimensionFields(fieldDefinitions)

INPUT:

fieldDefinitions: Field Definitilons as obtained from

getDefinedFieldProperties();

OUTPUTS:

fieldNames: The names of the multi-dimensional fields firstDim: the referenced field in the first dimension secondDim: the referenced field in the second dimension

initFBAFields(model, printLevel)

This function initializes all fields in a model that are required for downstream FBA analysis. It does so if and only if a Stoichiometric matrix S is provided.

USAGE:

model = convertOldStyleModel(model, printLevel)

INPUT:

model: a COBRA Model structure with at least the model.S field.

All fields already present are retained and absent fields are initialized with their defaults.

OPTIONAL INPUT:

printLevel: indicates whether warnings and messages are given (default, 1).

OUTPUT:

model: a COBRA model struct with the following fields:

.S (same as input) .rxns (default: a vector of strings R1 .. R size(S,2) .mets (default: a vector of strings M1 .. M size(S,1) .lb (default: -1000 * ones(size(S,2),1) ); .ub (default: 1000 * ones(size(S,2),1) ); .genes (default: cell(0,1)); .rules (default: repmat({‘’},size(S,2),1)) .osense (default: -1) .csense (default: a char vector of ‘E’ of the size size(S,1) x 1)

loadIdentifiedModel(filename, directory)

Load a single cobra toolbox model saved as a filename.mat file, then rename the model structure ‘model’ while retaining the original name of the model structure in model.modelID

USAGE:

model = loadIdentifiedModel(filename, directory)

INPUTS:

filename: name of the .mat file containing cobra toolbox model structure directory: directory where the .mat file resides.

OUTPUT:

model: COBRA model structure

mergeTextDataAndData(textdata, data, headings)

Merges textdata and data imported from .xls file assuming that the first row of textdata is column headings

USAGE:

mergedData = mergeTextDataAndData(textdata, data, headings)

INPUTS:

textdata: cell array from .xls import data: matrix with numeric data from .xls import

OPTIONAL INPUT:

headings: {(1), 0}, zero if no column headings

OUTPUT:

mergedData: merged cell array with all data from .xls import

model2xls(model, fileName, compSymbols, compNames)

Writes a model to and Excel spreadsheet.

USAGE:

model2xls(model, fileName, compSymbols, compNames)

INPUT:

model: A COBRA model struct fileName: filename with an xsl extension.

OPTIONAL INPUT:

compSymbols: Symbols of compartments used in metabolite ids compNames: Names of the compartments identified by the symbols

Example

‘Reaction List’ tab headers (case sensitive):

• Required:

  • ‘Abbreviation’: HEX1

  • ‘Reaction’: 1 atp[c] + 1 glc-D[c] –> 1 adp[c] + 1 g6p[c] + 1 h[c]

  • ‘GPR’: (3098.3) or (80201.1) or (2645.3) or …

• Optional:

  • ‘Description’: Hexokinase

  • ‘Subsystem’: Glycolysis

  • ‘Reversible’: 0 (false) or 1 (true)

  • ‘Lower bound’: 0

  • ‘Upper bound’: 1000

  • ‘Objective’: 0/1

  • ‘Confidence Score’: 0,1,2,3,4

  • ‘EC Number’: 2.7.1.1;2.7.1.2

  • ‘KEGG ID’: R000001

  • ‘Notes’: Reaction also associated with EC 2.7.1.2

  • ‘References’: PMID:2043117;PMID:7150652,…

‘Metabolite List’ tab: Required headers (case sensitive): (needs to be complete list of metabolites, i.e., if a metabolite appears in multiple compartments it has to be represented in multiple rows. Abbreviations need to overlap with use in Reaction List

• Required

  • ‘Abbreviation’: glc-D or glc-D[c]

• Optional:

  • ‘Charged formula’ or formula: C6H12O6

  • ‘Charge’: 0

  • ‘Compartment’: cytosol

  • ‘Description’: D-glucose

  • ‘KEGG ID’: C00031

  • ‘PubChem ID’: 5793

  • ‘ChEBI ID’: 4167

  • ‘InChI string’: InChI=1/C6H12O6/c7-1-2-3(8)4(9)5(10)6(11)12-2/h2-11H,1H2/t2-,3-,4+,5-,6?/m1/s1

  • ‘SMILES’: OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O

  • ‘HMDB ID’: HMDB00122

Note

Optional inputs may be required for input on unix machines.

outputHypergraph(model, weights, fileName)

Outputs to a file a metabolic reaction network hypergraph with weights in reactions Output format: Rxn metabolite_1 metabolite_2 … metabolite_n rxnWeight

USAGE:

outputHypergraph(model, weights, fileName)

INPUTS:

model: Standard model structure weights: Weights for each reaction fileName: Output filename

outputNetworkCytoscape(model, fileBase, rxnList, rxnData, metList, metData, metDegreeThr)

Outputs a metabolic network in Cytoscape format

USAGE:

notShownMets = outputNetworkCytoscape(model, fileBase, rxnList, rxnData, metList, metData, metDegreeThr)

INPUTS:

model: COBRA metabolic network model fileBase: Base file name (without extensions) for Cytoscape input

files that are generated by the function

OPTIONAL INPUTS:

rxnList: List of reactions that will included in the output

(Default = all reactions)

rxnData: Vector or matrix of data or cell array of strings to output for each

reaction in rxnList (Default = empty)

metList: List of metabolites that will be included in the output

(Default = all metabolites)

metData: Vector or matrix of data or cell array of strings to output

for each metabolite in metList (Default = empty)

metDegreeThr: Maximum degree of metabolites that will be included in the

output. Allows filtering out highly connected metabolites such as ‘h2o’ or ‘atp’ (Default = no filtering)

OUTPUT:

notShownMets: Metabolites that are not included in the output

Note

Outputs three to five files:

• [baseName].sif - Basic network structure file containing reaction-metabolite and gene-reaction (if provided in model) associations

• [baseName]_nodeType.noa - Describes the node types (gene, rxn, met) in the network

• [baseName]_nodeComp.noa - Describes the compartments for metabolites

• [baseName]_subSys.noa - Describes the subsystems for reactions (if provided)

• [baseName]_rxnMetData.noa - Reaction and metabolite data (if provided)

outputNetworkOmix(model, rxnBool)

Outputs a text file for import into omix http://www.13cflux.net/omix/

USAGE:

outputNetworkOmix(model, rxnBool)

INPUT:

model: COBRA model structure

OPTIONAL INPUT:

rxnBool: boolean vector with 1 for each reaction to be exported

parseSBMLAnnotationField(annotationField)

Parses the annotation field of an SBML file to extract metabolite information associations

USAGE:

[metCHEBI, metHMDB, metKEGG, metPubChem, metInChI] = parseSBMLAnnotationField(annotationField)

INPUTS:

annotationField: annotation filed of an SBML fileBase

OUTPUTS:

metCHEBI: Formula for each metabolite in the ChEBI format metHMDB: Formula for each metabolite in the HMDB format metKEGG: Formula for each metabolite in the KEGG format metPubChem: PubChem ID of each metabolite metInChI: Formula for each metabolite in the InCHI strings format

parseSBMLAnnotationFieldRxn(annotationField)

Parses the annotation field of an SBML file to extract reaction information associations

USAGE:

[rxnEC, rxnReference] = parseSBMLAnnotationFieldRxn(annotationField)

INPUT:

annotationField: annotation filed of an SBML fileBase

OUTPUTS:

rxnEC,rxnReference: only one of them is not empty depending on annotationField

parseSBMLNotesField(notesField)

Parses the notes field of an SBML file to extract gene-rxn associations

USAGE:

[subSystem, grRule, formula, confidenceScore, citation, comment, ecNumber, charge] = parseSBMLNotesField(notesField)

INPUT:

notesField: notes field of SBML file

OUTPUT:

subSystem: subSystem assignment for each reaction grRule: a string representation of the GPR rules defined in a readable format formula: elementa formula confidenceScore: confidence scores for reaction presence citation: joins strings with authors comment: comments and notes ecNumber: E.C. number for each reaction charge: charge of the respective metabolite

planariseModel(model, replicateMetBool)

Converts model into a form that is suitable for display as a planar hypergraph

USAGE:

[modelPlane, replicateMetBool, metData, rxnData] = planariseModel(model, replicateMetBool)

INPUTS:

model: model structure replicateMetBool: met x 1 boolean vector of metabolites to be replicated for each reaction

OUTPUTS:

modelPlane: structure with fields:

• .S - matrix

• .mets - metabolites

• .origMets - original metabolites

replicateMetBool: as in input metData: data of metabolites rxnData: data of reactions

readBooleanRegModel(metModel, fileName)

Reads Boolean regulatory network model

USAGE:

regModel = readBooleanRegModel(metModel, fileName)

INPUT:

metModel: model

OPTIONAL INPUT:

fileName: file name

OUTPUTS

regModel: model containing the following fields:

• .mets - Metabolite rules:

  • name - Metabolite/pool name (internal to the reg network model)

  • rule - Metabolite ‘activation’ rule

  • type - Metabolite type (extra/intracellular/pool)

  • excInd - Exchange flux indices corresponding to extracellular metabolites

  • icmRules - Intracellular metabolite ‘activation’ rules (based on a flux vector - fluxVector)

  • pool - Pool components

• .regs - Regulator rules

  • name - Regulator name

  • rule - Regulator rule

  • comp - Regulator rule components (i.e. metabolites or other regulators that affect the state of this regulator)

  • ruleParsed - Rule in parsed format (based on metabolite state - metState, regulator state - regState)

• .tars - Target rules

  • name - Target name

  • rule - Target rule

  • comp - Target rule components (i.e. metabolites or other regulators that affect the state of this regulator)

  • ruleParsed - Rule in parsed format (based on metabolite state - metState, regulator state - regState)

readSBML(fileName, defaultBound)

Reads in a SBML format model as a COBRA matlab structure

USAGE:

model = readSBML(fileName, defaultBound)

INPUTS:

fileName: File name for file to read in

OPTIONAL INPUTS:

defaultBound: Maximum bound for model (Default = 1000)

OUTPUT:

model: COBRA model structure

readSimPhenyCMPD(fileName)

Reads SimPheny compound file obtained from admin console

USAGE:

[metInfo, mets] = readSimPhenyCMPD(fileName)

INPUT:

fileName: SimPheny compound file name

OUTPUTS:

metInfo: Structure contaning data on metabolites mets: List of metabolites

readSimPhenyGPR(fileName)

Reads SimPheny gene-protein-reaction association file obtained from admin console

USAGE:

[rxnInfo, rxns, allGenes] = readSimPhenyGPR(fileName)

INPUT:

fileName: SimPheny GPR file

OUTPUTS:

rxnInfo: Structure containing data for each reaction rxns: List of reactions allGenes: List of all genes

readSimPhenyGprText(file, model)

Parses SimPheny GPRA’s in text format into a rxn x gene association matrix

USAGE:

gpraModel = readSimPhenyGPRText(file, model)

INPUTS:

file: GPR text file model: COBRA model structure

OUTPUT:

gpraModel: COBRA model structure with reaction-gene association matrix

restrictModelsToFields(models, fieldNames)

Removes all fields not given as fieldnames from the models

USAGE:

restrictedModels = restrictModelsToFields(models, fieldNames)

INPUT:

models: A Cell array of model structs (or single model

struct that has all fieldNames provided.

fieldNames: Names of the fields the models will be restricted

to.

OUTPUT:

restrictedModels: The models with the non names fields removed, or a single struct if its just one model.

write4ti2(SeFull, filename, uni)

Writes an input file for 4ti2. ‘ti2’ is a software package for algebraic, geometric and combinatorial problems on linear spaces - www.4ti2.de

USAGE:

write4ti2(SeFull, filename, uni)

INPUTS:

SeFull: full stoichiometric matrix filename: name of the file

OPTIONAL INPUT:

uni: {(0),1}, uni = 1 only outputs every second reaction

writeCytoscapeEdgeAttributeTable(model, C, B, N, replicateMetBool, filename)

Writes out a set of boolean edge attributes as one of a pair of colours, ‘Red’ for ‘yes’, ‘Black’ for ‘no’

USAGE:

writeCytoscapeEdgeAttributeTable(model, C, B, N, replicateMetBool, filename)

INPUTS:

model: structure with obligatory field .S - met x reaction C: reaction x attribute cell array B: reaction x attribute Boolean matrix N: reaction x attribute numeric array replicateMetBool: boolean for replicated mets filename: name of the file

writePajekNet(model)

Builds a metabolite centric directed graph from a COBRA model and outputs a graph in a .net format ready to use for most graph analysis software e.g. Pajek, it does one fba to set the link width equal to reaction fluxes.

USAGE:

writePajekNet(model)

INPUT:

model: a COBRA structured model

OUTPUT:

.net: file containing the graph

Ex: A + B -> C (hypergraph) with v = 0 => no output (empty line)

if v > 0 then it becomes A -> C; B -> C (graph),

if v < 0 then the order is reversed

writeSBML(model, fileName, compSymbolList, compNameList)

Exports a COBRA structure into an SBML FBCv2 file. A SBMLFBCv2 file a file is written to the current Matlab path.

USAGE:

sbmlModel = writeSBML(model, fileName, compSymbolList, compNameList)

INPUTS:

model: COBRA model structure fileName: File name for output file

OPTIONAL INPUTS:

compSymbolList: List of compartment symbols compNameList: List of copmartment names corresponding to compSymbolList

OUTPUT:

sbmlModel: SBML MATLAB structure

xls2model(fileName, biomassRxnEquation, defaultbound)

Reads a model from Excel spreadsheet.

USAGE:

model = xls2model(fileName, biomassRxnEquation, defaultbound)

INPUT:

fileName: xls spreadsheet, with one ‘Reaction List’ and one ‘Metabolite List’ tab

OPTIONAL INPUTS:

biomassRxnEquation: .xls may have a 255 character limit on each cell,

so pass the biomass reaction separately if it hits this maximum.

defaultbound: the deault bound for lower and upper bounds, if

no bounds are specified in the Excel sheet

OUTPUT:

model: COBRA Toolbox model

Example

‘Reaction List’ tab headers (case sensitive):

• Required:

  • ‘Abbreviation’: HEX1

  • ‘Reaction’: 1 atp[c] + 1 glc-D[c] –> 1 adp[c] + 1 g6p[c] + 1 h[c]

• Optional:

  • ‘GPR’: (3098.3) or (80201.1) or (2645.3) or …

  • ‘Description’: Hexokinase

  • ‘Subsystem’: Glycolysis

  • ‘Reversible’: 0 (false) or 1 (true)

  • ‘Lower bound’: 0

  • ‘Upper bound’: 1000

  • ‘Objective’: 0/1

  • ‘Confidence Score’: 0,1,2,3,4

  • ‘EC Number’: 2.7.1.1,2.7.1.2

  • ‘KEGG ID’: R000001

  • ‘Notes’: Reaction also associated with EC 2.7.1.2

  • ‘References’: PMID:2043117,PMID:7150652,…

‘Metabolite List’ tab: Required headers (case sensitive): (needs to be complete list of metabolites, i.e., if a metabolite appears in multiple compartments it has to be represented in multiple rows. Abbreviations need to overlap with use in Reaction List

• Required

  • ‘Abbreviation’: glc-D or glc-D[c]

• Optional:

  • ‘Charged formula’ or formula: C6H12O6

  • ‘Charge’: 0

  • ‘Compartment’: cytosol

  • ‘Description’: D-glucose

  • ‘KEGG ID’: C00031

  • ‘PubChem ID’: 5793

  • ‘ChEBI ID’: 4167

  • ‘InChI string’: InChI=1/C6H12O6/c7-1-2-3(8)4(9)5(10)6(11)12-2/h2-11H,1H2/t2-,3-,4+,5-,6?/m1/s1

  • ‘SMILES’: OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O

  • ‘HMDB ID’: HMDB00122

Note

Optional inputs may be required for input on unix machines.

Note

Find an example Excel sheet at docs/source/examples/ExcelExample.xlsx