msgenomeclassifier

load_classifier_from_folder()

A function that loads the model and model features from a local folder:

media = load_classifier_from_folder(directory, filename)

• directory str: The directory in which the model and features files are provided.

• filename str: The basename of the file, where the model file is named <filename>.pickle and the features file is named <filename>_features.json.

returns msgenclass modelseedpy.core.msgenomeclassifier.MSGenomeClassifier: The MSGenomeClassifier object of the respective model and model features.

MSGenomeClassifier()

This class classifies a model and its features:

from modelseedpy.core import MSGenomeClassifier
genclass = MSGenomeClassifier(model, model_features)

• model cobra.core.model.Model: The CobraKBase model whose genome will be classified.

• model_features dict: A descriptive dictionary of the investigated model.

extract_features_from_genome()

A function that assembles a unique list of features for the specified genome:

genome_features = genclass.extract_features_from_genome(genome, ontology_term)

• genome ModelSEED Genome: The ModelSEED Genome that will be classified.

• ontology_term str: The ontological criteria that will assess the genome.

returns genome_features dict: A list of genome features value with the key of "genome".

classify()

A function that predicts FBA solutions based upon a set of genome features and indicators:

media = genclass.classify(genome, ontology_term='RAST')

• genome ModelSEED Genome: The ModelSEED Genome that will be classified.

• ontology_term str: The ontological criteria that will assess the genome.

returns prediction str: The numerical prediction of the model based upon the set of genome features and indicators.