SBML-utilities

convertSBMLID(str, toSBML)[source]

CONVERTSBMLID converts the given str to a valid SBML ID Usage

convertedstr = convertSBMLID(str,toSBML)

Input

  • str – The String to convert

Optional input

  • toSBML – Whether to convert to SBML format (or undo a conversion) (default true, ie convert to SBML)

Output

  • convertedstr – The converted String.
getBioQualifiers()[source]

Get a list of possible bioqualifiers

Usage

annotationQualifiers = getBioQualifiers()

Outputs

  • bioQualifiers – A cell array of bioqualifier strings in descending order.
  • standardQualifiers – A n x 2 cell array with the first column representing the standard identifiers and the second column representing the alternative name.
getDataBases(Ressources, qualifier)[source]

getDataBases extracts database and correspdoning id from a ressource string in an sbml Usage

[databases,ids,qualifiers] = getDataBases(Ressource,qualifier)

Inputs

  • Ressources – The Ressource String(s) as a cell array
  • qualifier – The bio-qualifier of the ressource

Outputs

  • databases – The databases of the ressources
  • ids – The identifiers of the ressource strings
  • qualifier – The bio-qualifiers associated (the same as the input)

Note

Currently two different schemes are accepted: urn:miriam:DatabaeID:EntryID https://identifiers.org/databaseid/EntryID The correctness of the entries is NOT checked!

makeSBMLAnnotationString(model, id, fieldentries, position)[source]

makeSBMLAnnotationString gives the annotationString for an SBML based on the fields in the model

Usage

[annotationString, notes] = makeSBMLAnnotationString(model,id,fieldentries,position)

Inputs

  • model – the model to extract the data
  • id – the ID of the entity
  • fieldentries – either a char indicating the field (prot,met,rxn,comp,gene), or a cell array with X{:,1} being field IDs and X{:,2} being bioql qualiiers to annotate for the field.
  • position – the position in the model to extract the data.

Outputs

  • annotationString – The annotation String to be put into the SBML.
  • notes – A 2*x cell array of fields which did not contain valid identifiers (according to the pattern check.
mapAnnotationsToFields(model, databases, identifiers, relations, field, relationSelection, inverseRelationSelection)[source]

MAPANNOTATIONSTOFIELDS maps annotations in bioql/MIRIAM annotation from SBML to model fields.

Usage

mappedFields = mapAnnotationsToFields(model,databases,identifiers,relations,field,relationSelection, exclusiveSelection)

Inputs

  • model – the COBRA model to annotate
  • databases – a cell array of cell arrays containing databases
  • identifiers – a cell array of cell arrays containing the identifiers associated with the databases above
  • relations – a cell array of cell arrays containing the bioql relations associated with the databases above
  • field – the model field (met/gene/rxn/protein/comp etc) to annotate. Note that there is an s missing here.

Optional inputs

  • relationSelection – whether only a specific relation is choosen and all others are ignored (default {})
  • inverseRelationSelection – whether the relation specified by relationSelection is inverted (i.e. all other fields are used (default true))

Output

  • mappedFields – a struct with fields for each encountered annotation database (Known databases like e.g. HMDB will be mapped to their corresponding field metHMDBID, while unknown fields will be mapped to: [field relation convertSBMLID(database)]
parseCVTerms(CVTerms)[source]

parseCVTerms extracts the annotations deposited in cvterms in an SBML struct

Usage

[databases, identifiers, relations] = parseCVTerms(CVTerms)

Input

  • CVTerms – the CVTerms field of an SBML model field

Outputs

  • databases – the databases stored in the ressources of the CVTerms.
  • identifiers – The identifiers annotated for the databases.
  • relations – The bio-qualifier relation encoded in the CVTerms.