Sbml

convertSBMLID(str, toSBML)

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()

Get a list of possible bioqualifiers

USAGE:

annotationQualifiers = getBioQualifiers()

OUTPUT:

• 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)

getDataBases extracts database and correspdoning id from a ressource string in an sbml :USAGE: [databases,ids,qualifiers] = getDataBases (Ressource,qualifier)

INPUT:

• Ressources – The Ressource String(s) as a cell array

• qualifier – The bio-qualifier of the ressource

OUTPUT:

• 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, mergeAnnotations)

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

USAGE:

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

INPUT:

• 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.

OPTIONAL INPUTS:

mergeAnnotations – If multiple fields are given, merge the fields and only produce one annotation.

OUTPUT:

• 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)

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

USAGE:

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

INPUT:

• 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 INPUT:

• 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)

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

OUTPUT:

• 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.