예제 #1
0
class Gene(obj_tables.Model):
    comment = obj_tables.StringAttribute(verbose_name='Comment')
    reference_name = obj_tables.StringAttribute(verbose_name='ReferenceName')
    reference_pub_med = obj_tables.StringAttribute(
        verbose_name='ReferencePubMed')
    reference_d_o_i = obj_tables.StringAttribute(verbose_name='ReferenceDOI')
    description = obj_tables.StringAttribute(verbose_name='Description')
    name = obj_tables.StringAttribute(verbose_name='Name')
    miriam_annotations = obj_tables.StringAttribute(
        verbose_name='MiriamAnnotations')
    type = obj_tables.StringAttribute(verbose_name='Type')
    symbol = obj_tables.StringAttribute(verbose_name='Symbol')
    position_x = obj_tables.FloatAttribute(verbose_name='PositionX')
    position_y = obj_tables.FloatAttribute(verbose_name='PositionY')
    i_d = obj_tables.StringAttribute(verbose_name='ID')
    locus_name = obj_tables.StringAttribute(verbose_name='LocusName')
    gene_product = obj_tables.StringAttribute(verbose_name='GeneProduct')
    gene_product_s_b_m_l_species_id = obj_tables.StringAttribute(
        verbose_name='GeneProduct:SBML:species:id')
    operon = obj_tables.StringAttribute(verbose_name='Operon')
    identifiers = obj_tables.StringAttribute(verbose_name='Identifiers')
    s_b_m_l_fbc_i_d = obj_tables.StringAttribute(verbose_name='SBML:fbc:ID')
    s_b_m_l_fbc_name = obj_tables.StringAttribute(verbose_name='SBML:fbc:Name')
    s_b_m_l_fbc_gene_product = obj_tables.BooleanAttribute(
        verbose_name='SBML:fbc:GeneProduct')
    s_b_m_l_fbc_gene_association = obj_tables.BooleanAttribute(
        verbose_name='SBML:fbc:GeneAssociation')
    s_b_m_l_fbc_label = obj_tables.StringAttribute(
        verbose_name='SBML:fbc:Label')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'comment',
            'reference_name',
            'reference_pub_med',
            'reference_d_o_i',
            'description',
            'name',
            'miriam_annotations',
            'type',
            'symbol',
            'position_x',
            'position_y',
            'i_d',
            'locus_name',
            'gene_product',
            'gene_product_s_b_m_l_species_id',
            'operon',
            'identifiers',
            's_b_m_l_fbc_i_d',
            's_b_m_l_fbc_name',
            's_b_m_l_fbc_gene_product',
            's_b_m_l_fbc_gene_association',
            's_b_m_l_fbc_label',
        )
        verbose_name = 'Gene'
        verbose_name_plural = 'Gene'
예제 #2
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class Relation(obj_tables.Model):
    comment = obj_tables.StringAttribute(verbose_name='Comment')
    reference_name = obj_tables.StringAttribute(verbose_name='ReferenceName')
    reference_pub_med = obj_tables.StringAttribute(
        verbose_name='ReferencePubMed')
    reference_d_o_i = obj_tables.StringAttribute(verbose_name='ReferenceDOI')
    description = obj_tables.StringAttribute(verbose_name='Description')
    i_d = obj_tables.StringAttribute(verbose_name='ID')
    from_object = obj_tables.StringAttribute(verbose_name='FromObject')
    to_object = obj_tables.StringAttribute(verbose_name='ToObject')
    is_symmetric = obj_tables.BooleanAttribute(verbose_name='IsSymmetric')
    value_quantity_type = obj_tables.FloatAttribute(
        verbose_name='Value:QuantityType')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'comment',
            'reference_name',
            'reference_pub_med',
            'reference_d_o_i',
            'description',
            'i_d',
            'from_object',
            'to_object',
            'is_symmetric',
            'value_quantity_type',
        )
        verbose_name = 'Relation'
        verbose_name_plural = 'Relation'
예제 #3
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class GeneLocus(core.PolymerLocus):
    """ Knowledge of a gene

    Attributes:
        symbol (:obj:`str`): symbol

    Related attributes:
        proteins (:obj:`list` of :obj:`ProteinSpeciesType`): protein
    """

    symbol = obj_tables.StringAttribute()
    start = obj_tables.IntegerAttribute()
    end = obj_tables.IntegerAttribute()
    is_essential = obj_tables.BooleanAttribute()
    proteins = obj_tables.OneToOneAttribute(ProteinSpeciesType,
                                            related_name='gene')
    homologs = obj_tables.LongStringAttribute()
    evidence = obj_tables.OneToManyAttribute(core.Evidence,
                                             related_name='genes')
    cog = obj_tables.sci.onto.OntoTermAttribute(
        kbOnt, terms=kbOnt['WC:COG'].subclasses(), none=True)

    class Meta(obj_tables.Model.Meta):
        verbose_name = 'Gene'
        verbose_name_plural = 'Genes'
        attribute_order = ('id', 'name', 'synonyms', 'symbol', 'polymer',
                           'start', 'end', 'cog', 'homologs', 'is_essential',
                           'proteins', 'evidence', 'identifiers', 'references',
                           'comments')
예제 #4
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class FbcObjective(obj_tables.Model):
    i_d = obj_tables.StringAttribute(verbose_name='ID')
    name = obj_tables.StringAttribute(verbose_name='Name')
    s_b_m_l_fbc_type = obj_tables.StringAttribute(verbose_name='SBML:fbc:type')
    s_b_m_l_fbc_active = obj_tables.BooleanAttribute(
        verbose_name='SBML:fbc:active')
    s_b_m_l_fbc_objective = obj_tables.StringAttribute(
        verbose_name='SBML:fbc:objective')
    s_b_m_l_fbc_reaction = obj_tables.StringAttribute(
        verbose_name='SBML:fbc:reaction')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'i_d',
            'name',
            's_b_m_l_fbc_type',
            's_b_m_l_fbc_active',
            's_b_m_l_fbc_objective',
            's_b_m_l_fbc_reaction',
        )
        verbose_name = 'FbcObjective'
        verbose_name_plural = 'FbcObjective'
예제 #5
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class Relationship(obj_tables.Model):
    i_d = obj_tables.StringAttribute(verbose_name='ID')
    from_object = obj_tables.StringAttribute(verbose_name='FromObject')
    to_object = obj_tables.StringAttribute(verbose_name='ToObject')
    value = obj_tables.IntegerAttribute(verbose_name='Value')
    is_symmetric = obj_tables.BooleanAttribute(verbose_name='IsSymmetric')
    sign = obj_tables.EnumAttribute(['+', '-', '0'],
                                    default='0',
                                    verbose_name='Sign')
    relation = obj_tables.StringAttribute(verbose_name='Relation')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'i_d',
            'from_object',
            'to_object',
            'value',
            'is_symmetric',
            'sign',
            'relation',
        )
        verbose_name = 'Relationship'
        verbose_name_plural = 'Relationship'
예제 #6
0
파일: schema.py 프로젝트: 0u812/obj_tables
class Reaction(obj_tables.Model):
    id = obj_tables.StringAttribute(primary=True, unique=True)
    id_i_a_f1260 = obj_tables.StringAttribute(
        none=True,
        default=None,
        default_cleaned_value=None,
        verbose_name='Id (iAF1260 [Ref1])')
    name = obj_tables.StringAttribute(none=True,
                                      default=None,
                                      default_cleaned_value=None)
    equation = obj_tables.chem.ReactionEquationAttribute(
        species_cls=Metabolite, compartment_cls=Compartment)
    reversible = obj_tables.BooleanAttribute()
    subsystem = obj_tables.StringAttribute(none=True,
                                           default=None,
                                           default_cleaned_value=None)
    ec_number = obj_tables.RegexAttribute(pattern='\d+\.\d+\.\d+\.\d+',
                                          none=True,
                                          default=None,
                                          default_cleaned_value=None,
                                          verbose_name='EC number')
    lower_bound = obj_tables.FloatAttribute()
    upper_bound = obj_tables.FloatAttribute()
    flux_acetate = obj_tables.FloatAttribute(
        verbose_name='Flux (Acetate media, mmol * gCDW^-1 * h^-1)')
    flux_acetate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Acetate media, mmol * gCDW^-1 * h^-1)')
    flux_fructose = obj_tables.FloatAttribute(
        verbose_name='Flux (Fructose media, mmol * gCDW^-1 * h^-1)')
    flux_fructose_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Fructose media, mmol * gCDW^-1 * h^-1)'
    )
    flux_galactose = obj_tables.FloatAttribute(
        verbose_name='Flux (Galactose media, mmol * gCDW^-1 * h^-1)')
    flux_galactose_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Galactose media, mmol * gCDW^-1 * h^-1)'
    )
    flux_glucose = obj_tables.FloatAttribute(
        verbose_name='Flux (Glucose media, mmol * gCDW^-1 * h^-1)')
    flux_glucose_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Glucose media, mmol * gCDW^-1 * h^-1)')
    flux_glycerol = obj_tables.FloatAttribute(
        verbose_name='Flux (Glycerol media, mmol * gCDW^-1 * h^-1)')
    flux_glycerol_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Glycerol media, mmol * gCDW^-1 * h^-1)'
    )
    flux_gluconate = obj_tables.FloatAttribute(
        verbose_name='Flux (Gluconate media, mmol * gCDW^-1 * h^-1)')
    flux_gluconate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Gluconate media, mmol * gCDW^-1 * h^-1)'
    )
    flux_pyruvate = obj_tables.FloatAttribute(
        verbose_name='Flux (Pyruvate media, mmol * gCDW^-1 * h^-1)')
    flux_pyruvate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Pyruvate media, mmol * gCDW^-1 * h^-1)'
    )
    flux_succinate = obj_tables.FloatAttribute(
        verbose_name='Flux (Succinate media, mmol * gCDW^-1 * h^-1)')
    flux_succinate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='Flux uncertainty (Succinate media, mmol * gCDW^-1 * h^-1)'
    )
    delta_g_acetate = obj_tables.FloatAttribute(
        verbose_name='ΔG (Acetate, kJ * mol^-1)')
    delta_g_acetate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Acetate, kJ * mol^-1)')
    delta_g_fructose = obj_tables.FloatAttribute(
        verbose_name='ΔG (Fructose, kJ * mol^-1)')
    delta_g_fructose_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Fructose, kJ * mol^-1)')
    delta_g_galactose = obj_tables.FloatAttribute(
        verbose_name='ΔG (Galactose, kJ * mol^-1)')
    delta_g_galactose_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Galactose, kJ * mol^-1)')
    delta_g_glucose = obj_tables.FloatAttribute(
        verbose_name='ΔG (Glucose, kJ * mol^-1)')
    delta_g_glucose_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Glucose, kJ * mol^-1)')
    delta_g_glycerol = obj_tables.FloatAttribute(
        verbose_name='ΔG (Glycerol, kJ * mol^-1)')
    delta_g_glycerol_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Glycerol, kJ * mol^-1)')
    delta_g_gluconate = obj_tables.FloatAttribute(
        verbose_name='ΔG (Gluconate, kJ * mol^-1)')
    delta_g_gluconate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Gluconate, kJ * mol^-1)')
    delta_g_pyruvate = obj_tables.FloatAttribute(
        verbose_name='ΔG (Pyruvate, kJ * mol^-1)')
    delta_g_pyruvate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Pyruvate, kJ * mol^-1)')
    delta_g_succinate = obj_tables.FloatAttribute(
        verbose_name='ΔG (Succinate, kJ * mol^-1)')
    delta_g_succinate_uncertainty = obj_tables.FloatAttribute(
        verbose_name='ΔG uncertainty (Succinate, kJ * mol^-1)')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'id',
            'id_i_a_f1260',
            'name',
            'equation',
            'reversible',
            'subsystem',
            'ec_number',
            'lower_bound',
            'upper_bound',
            'flux_acetate',
            'flux_acetate_uncertainty',
            'flux_fructose',
            'flux_fructose_uncertainty',
            'flux_galactose',
            'flux_galactose_uncertainty',
            'flux_glucose',
            'flux_glucose_uncertainty',
            'flux_glycerol',
            'flux_glycerol_uncertainty',
            'flux_gluconate',
            'flux_gluconate_uncertainty',
            'flux_pyruvate',
            'flux_pyruvate_uncertainty',
            'flux_succinate',
            'flux_succinate_uncertainty',
            'delta_g_acetate',
            'delta_g_acetate_uncertainty',
            'delta_g_fructose',
            'delta_g_fructose_uncertainty',
            'delta_g_galactose',
            'delta_g_galactose_uncertainty',
            'delta_g_glucose',
            'delta_g_glucose_uncertainty',
            'delta_g_glycerol',
            'delta_g_glycerol_uncertainty',
            'delta_g_gluconate',
            'delta_g_gluconate_uncertainty',
            'delta_g_pyruvate',
            'delta_g_pyruvate_uncertainty',
            'delta_g_succinate',
            'delta_g_succinate_uncertainty',
        )
        verbose_name = 'Reaction'
        verbose_name_plural = 'Reactions'
예제 #7
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class Quantity(obj_tables.Model):
    comment = obj_tables.StringAttribute(verbose_name='Comment')
    reference_name = obj_tables.StringAttribute(verbose_name='ReferenceName')
    reference_pub_med = obj_tables.StringAttribute(
        verbose_name='ReferencePubMed')
    reference_d_o_i = obj_tables.StringAttribute(verbose_name='ReferenceDOI')
    description = obj_tables.StringAttribute(verbose_name='Description')
    name = obj_tables.StringAttribute(verbose_name='Name')
    miriam_annotations = obj_tables.StringAttribute(
        verbose_name='MiriamAnnotations')
    type = obj_tables.StringAttribute(verbose_name='Type')
    symbol = obj_tables.StringAttribute(verbose_name='Symbol')
    position_x = obj_tables.FloatAttribute(verbose_name='PositionX')
    position_y = obj_tables.FloatAttribute(verbose_name='PositionY')
    i_d = obj_tables.StringAttribute(verbose_name='ID')
    quantity = obj_tables.StringAttribute(verbose_name='Quantity')
    reference = obj_tables.StringAttribute(verbose_name='Reference')
    quantity_name = obj_tables.StringAttribute(verbose_name='QuantityName')
    quantity_type = obj_tables.StringAttribute(verbose_name='QuantityType')
    value = obj_tables.FloatAttribute(verbose_name='Value')
    mean = obj_tables.FloatAttribute(verbose_name='Mean')
    std = obj_tables.FloatAttribute(verbose_name='Std')
    min = obj_tables.FloatAttribute(verbose_name='Min')
    max = obj_tables.FloatAttribute(verbose_name='Max')
    median = obj_tables.FloatAttribute(verbose_name='Median')
    geometric_mean = obj_tables.FloatAttribute(verbose_name='GeometricMean')
    sign = obj_tables.EnumAttribute(['+', '-', '0'],
                                    default='0',
                                    verbose_name='Sign')
    prob_dist = obj_tables.StringAttribute(verbose_name='ProbDist')
    s_b_m_l_parameter_id = obj_tables.StringAttribute(
        verbose_name='SBML:parameter:id')
    unit = obj_tables.StringAttribute(verbose_name='Unit')
    scale = obj_tables.StringAttribute(verbose_name='Scale')
    time = obj_tables.FloatAttribute(verbose_name='Time')
    time_point = obj_tables.StringAttribute(verbose_name='TimePoint')
    condition = obj_tables.StringAttribute(verbose_name='Condition')
    p_h = obj_tables.FloatAttribute(verbose_name='pH')
    temperature = obj_tables.FloatAttribute(verbose_name='Temperature')
    location = obj_tables.StringAttribute(verbose_name='Location')
    location_s_b_m_l_compartment_id = obj_tables.StringAttribute(
        verbose_name='Location:SBML:compartment:id')
    compound = obj_tables.StringAttribute(verbose_name='Compound')
    compound_s_b_m_l_species_id = obj_tables.StringAttribute(
        verbose_name='Compound:SBML:species:id')
    reaction = obj_tables.StringAttribute(verbose_name='Reaction')
    reaction_s_b_m_l_reaction_id = obj_tables.StringAttribute(
        verbose_name='Reaction:SBML:reaction:id')
    enyzme = obj_tables.StringAttribute(verbose_name='Enyzme')
    enyzme_s_b_m_l_species_id = obj_tables.StringAttribute(
        verbose_name='Enyzme:SBML:species:id')
    enyzme_s_b_m_l_parameter_id = obj_tables.StringAttribute(
        verbose_name='Enyzme:SBML:parameter:id')
    gene = obj_tables.StringAttribute(verbose_name='Gene')
    organism = obj_tables.StringAttribute(verbose_name='Organism')
    provenance = obj_tables.StringAttribute(verbose_name='Provenance')
    s_b_o_term = obj_tables.StringAttribute(verbose_name='SBOTerm')
    identifiers = obj_tables.StringAttribute(verbose_name='Identifiers')
    identifiers_kegg_reaction = obj_tables.StringAttribute(
        verbose_name='Identifiers:kegg.reaction')
    identifiers_kegg_compound = obj_tables.StringAttribute(
        verbose_name='Identifiers:kegg.compound')
    identifiers_obo_chebi = obj_tables.StringAttribute(
        verbose_name='Identifiers:obo.chebi')
    reaction_identifiers_kegg_reaction = obj_tables.StringAttribute(
        verbose_name='Reaction:Identifiers:kegg.reaction')
    compound_identifiers_kegg_compound = obj_tables.StringAttribute(
        verbose_name='Compound:Identifiers:kegg.compound')
    biological_element = obj_tables.StringAttribute(
        verbose_name='BiologicalElement')
    mathematical_type = obj_tables.StringAttribute(
        verbose_name='MathematicalType')
    data_geometric_std = obj_tables.FloatAttribute(
        verbose_name='DataGeometricStd')
    prior_median = obj_tables.FloatAttribute(verbose_name='PriorMedian')
    prior_std = obj_tables.FloatAttribute(verbose_name='PriorStd')
    prior_geometric_std = obj_tables.FloatAttribute(
        verbose_name='PriorGeometricStd')
    lower_bound = obj_tables.FloatAttribute(verbose_name='LowerBound')
    upper_bound = obj_tables.FloatAttribute(verbose_name='UpperBound')
    data_std = obj_tables.FloatAttribute(verbose_name='DataStd')
    physical_type = obj_tables.StringAttribute(verbose_name='PhysicalType')
    dependence = obj_tables.StringAttribute(verbose_name='Dependence')
    use_as_prior_information = obj_tables.BooleanAttribute(
        verbose_name='UseAsPriorInformation')
    s_b_m_l_element = obj_tables.StringAttribute(verbose_name='SBMLElement')
    abbreviation = obj_tables.StringAttribute(verbose_name='Abbreviation')
    matrix_info = obj_tables.StringAttribute(verbose_name='MatrixInfo')
    s_b_o_equilibrium_constant = obj_tables.FloatAttribute(
        verbose_name='SBO:equilibrium_constant')
    s_b_o_identifiers_obo_sbo = obj_tables.StringAttribute(
        verbose_name='SBO:Identifiers:obo.sbo')
    s_b_o_concentration = obj_tables.FloatAttribute(
        verbose_name='SBO:concentration')
    s_b_o_concentration_m_m_log10_median = obj_tables.FloatAttribute(
        verbose_name='SBO:concentration [mM:Log10]:Median')
    value_type = obj_tables.StringAttribute(verbose_name='ValueType')
    concentration_min = obj_tables.FloatAttribute(
        verbose_name='Concentration:Min')
    concentration_max = obj_tables.FloatAttribute(
        verbose_name='Concentration:Max')
    parameter_s_b_m_l_parameter_id = obj_tables.StringAttribute(
        verbose_name='Parameter:SBML:parameter:id')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'comment',
            'reference_name',
            'reference_pub_med',
            'reference_d_o_i',
            'description',
            'name',
            'miriam_annotations',
            'type',
            'symbol',
            'position_x',
            'position_y',
            'i_d',
            'quantity',
            'reference',
            'quantity_name',
            'quantity_type',
            'value',
            'mean',
            'std',
            'min',
            'max',
            'median',
            'geometric_mean',
            'sign',
            'prob_dist',
            's_b_m_l_parameter_id',
            'unit',
            'scale',
            'time',
            'time_point',
            'condition',
            'p_h',
            'temperature',
            'location',
            'location_s_b_m_l_compartment_id',
            'compound',
            'compound_s_b_m_l_species_id',
            'reaction',
            'reaction_s_b_m_l_reaction_id',
            'enyzme',
            'enyzme_s_b_m_l_species_id',
            'enyzme_s_b_m_l_parameter_id',
            'gene',
            'organism',
            'provenance',
            's_b_o_term',
            'identifiers',
            'identifiers_kegg_reaction',
            'identifiers_kegg_compound',
            'identifiers_obo_chebi',
            'reaction_identifiers_kegg_reaction',
            'compound_identifiers_kegg_compound',
            'biological_element',
            'mathematical_type',
            'data_geometric_std',
            'prior_median',
            'prior_std',
            'prior_geometric_std',
            'lower_bound',
            'upper_bound',
            'data_std',
            'physical_type',
            'dependence',
            'use_as_prior_information',
            's_b_m_l_element',
            'abbreviation',
            'matrix_info',
            's_b_o_equilibrium_constant',
            's_b_o_identifiers_obo_sbo',
            's_b_o_concentration',
            's_b_o_concentration_m_m_log10_median',
            'value_type',
            'concentration_min',
            'concentration_max',
            'parameter_s_b_m_l_parameter_id',
        )
        verbose_name = 'Quantity'
        verbose_name_plural = 'Quantity'
예제 #8
0
class Reaction(obj_tables.Model):
    comment = obj_tables.StringAttribute(verbose_name='Comment')
    reference_name = obj_tables.StringAttribute(verbose_name='ReferenceName')
    reference_pub_med = obj_tables.StringAttribute(
        verbose_name='ReferencePubMed')
    reference_d_o_i = obj_tables.StringAttribute(verbose_name='ReferenceDOI')
    description = obj_tables.StringAttribute(verbose_name='Description')
    modifier = obj_tables.StringAttribute(verbose_name='Modifier')
    name = obj_tables.StringAttribute(verbose_name='Name')
    miriam_annotations = obj_tables.StringAttribute(
        verbose_name='MiriamAnnotations')
    type = obj_tables.StringAttribute(verbose_name='Type')
    symbol = obj_tables.StringAttribute(verbose_name='Symbol')
    position_x = obj_tables.FloatAttribute(verbose_name='PositionX')
    position_y = obj_tables.FloatAttribute(verbose_name='PositionY')
    i_d = obj_tables.StringAttribute(verbose_name='ID')
    s_b_m_l_reaction_id = obj_tables.StringAttribute(
        verbose_name='SBML:reaction:id')
    reaction_formula = obj_tables.LongStringAttribute(
        verbose_name='ReactionFormula')
    location = obj_tables.StringAttribute(verbose_name='Location')
    enzyme = obj_tables.StringAttribute(verbose_name='Enzyme')
    model = obj_tables.StringAttribute(verbose_name='Model')
    pathway = obj_tables.StringAttribute(verbose_name='Pathway')
    subreaction_of = obj_tables.StringAttribute(verbose_name='SubreactionOf')
    is_complete = obj_tables.BooleanAttribute(verbose_name='IsComplete')
    is_reversible = obj_tables.BooleanAttribute(verbose_name='IsReversible')
    is_in_equilibrium = obj_tables.BooleanAttribute(
        verbose_name='IsInEquilibrium')
    is_exchange_reaction = obj_tables.BooleanAttribute(
        verbose_name='IsExchangeReaction')
    flux = obj_tables.FloatAttribute(verbose_name='Flux')
    is_non_enzymatic = obj_tables.BooleanAttribute(
        verbose_name='IsNonEnzymatic')
    kinetic_law = obj_tables.LongStringAttribute(verbose_name='KineticLaw')
    kinetic_law_name = obj_tables.StringAttribute(
        verbose_name='KineticLaw:Name')
    kinetic_law_formula = obj_tables.StringAttribute(
        verbose_name='KineticLaw:Formula')
    gene = obj_tables.StringAttribute(verbose_name='Gene')
    gene_symbol = obj_tables.StringAttribute(verbose_name='Gene:Symbol')
    operon = obj_tables.StringAttribute(verbose_name='Operon')
    enzyme_s_b_m_l_species_id = obj_tables.StringAttribute(
        verbose_name='Enzyme:SBML:species:id')
    enzyme_s_b_m_l_parameter_id = obj_tables.StringAttribute(
        verbose_name='Enzyme:SBML:parameter:id')
    build_reaction = obj_tables.BooleanAttribute(verbose_name='BuildReaction')
    build_enzyme = obj_tables.BooleanAttribute(verbose_name='BuildEnzyme')
    build_enzyme_production = obj_tables.BooleanAttribute(
        verbose_name='BuildEnzymeProduction')
    s_b_o_term = obj_tables.StringAttribute(verbose_name='SBOTerm')
    identifiers = obj_tables.StringAttribute(verbose_name='Identifiers')
    identifiers_kegg_reaction = obj_tables.StringAttribute(
        verbose_name='Identifiers:kegg.reaction')
    identifiers_obo_sbo = obj_tables.StringAttribute(
        verbose_name='Identifiers:obo.sbo')
    identifiers_ec_code = obj_tables.StringAttribute(
        verbose_name='Identifiers:ec-code')
    s_b_m_l_fbc_gene_association = obj_tables.LongStringAttribute(
        verbose_name='SBML:fbc:GeneAssociation')
    s_b_m_l_fbc_lower_bound = obj_tables.StringAttribute(
        verbose_name='SBML:fbc:LowerBound')
    s_b_m_l_fbc_upper_bound = obj_tables.StringAttribute(
        verbose_name='SBML:fbc:UpperBound')
    regulator = obj_tables.StringAttribute(verbose_name='Regulator')
    name_for_plots = obj_tables.StringAttribute(verbose_name='NameForPlots')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'comment',
            'reference_name',
            'reference_pub_med',
            'reference_d_o_i',
            'description',
            'modifier',
            'name',
            'miriam_annotations',
            'type',
            'symbol',
            'position_x',
            'position_y',
            'i_d',
            's_b_m_l_reaction_id',
            'reaction_formula',
            'location',
            'enzyme',
            'model',
            'pathway',
            'subreaction_of',
            'is_complete',
            'is_reversible',
            'is_in_equilibrium',
            'is_exchange_reaction',
            'flux',
            'is_non_enzymatic',
            'kinetic_law',
            'kinetic_law_name',
            'kinetic_law_formula',
            'gene',
            'gene_symbol',
            'operon',
            'enzyme_s_b_m_l_species_id',
            'enzyme_s_b_m_l_parameter_id',
            'build_reaction',
            'build_enzyme',
            'build_enzyme_production',
            's_b_o_term',
            'identifiers',
            'identifiers_kegg_reaction',
            'identifiers_obo_sbo',
            'identifiers_ec_code',
            's_b_m_l_fbc_gene_association',
            's_b_m_l_fbc_lower_bound',
            's_b_m_l_fbc_upper_bound',
            'regulator',
            'name_for_plots',
        )
        verbose_name = 'Reaction'
        verbose_name_plural = 'Reaction'
예제 #9
0
class Compound(obj_tables.Model):
    comment = obj_tables.StringAttribute(verbose_name='Comment')
    reference_name = obj_tables.StringAttribute(verbose_name='ReferenceName')
    reference_pub_med = obj_tables.StringAttribute(
        verbose_name='ReferencePubMed')
    reference_d_o_i = obj_tables.StringAttribute(verbose_name='ReferenceDOI')
    description = obj_tables.StringAttribute(verbose_name='Description')
    name = obj_tables.StringAttribute(verbose_name='Name')
    miriam_annotations = obj_tables.StringAttribute(
        verbose_name='MiriamAnnotations')
    type = obj_tables.StringAttribute(verbose_name='Type')
    symbol = obj_tables.StringAttribute(verbose_name='Symbol')
    position_x = obj_tables.FloatAttribute(verbose_name='PositionX')
    position_y = obj_tables.FloatAttribute(verbose_name='PositionY')
    i_d = obj_tables.StringAttribute(verbose_name='ID')
    s_b_m_l_species_id = obj_tables.StringAttribute(
        verbose_name='SBML:species:id')
    s_b_m_l_speciestype_id = obj_tables.StringAttribute(
        verbose_name='SBML:speciestype:id')
    initial_value = obj_tables.FloatAttribute(verbose_name='InitialValue')
    initial_concentration = obj_tables.FloatAttribute(
        verbose_name='InitialConcentration')
    unit = obj_tables.StringAttribute(verbose_name='Unit')
    location = obj_tables.StringAttribute(verbose_name='Location')
    state = obj_tables.StringAttribute(verbose_name='State')
    compound_sum_formula = obj_tables.StringAttribute(
        verbose_name='CompoundSumFormula')
    structure_formula = obj_tables.StringAttribute(
        verbose_name='StructureFormula')
    charge = obj_tables.IntegerAttribute(verbose_name='Charge')
    mass = obj_tables.FloatAttribute(verbose_name='Mass')
    is_constant = obj_tables.BooleanAttribute(verbose_name='IsConstant')
    enzyme_role = obj_tables.StringAttribute(verbose_name='EnzymeRole')
    regulator_role = obj_tables.StringAttribute(verbose_name='RegulatorRole')
    s_b_o_term = obj_tables.StringAttribute(verbose_name='SBOTerm')
    identifiers = obj_tables.StringAttribute(verbose_name='Identifiers')
    identifiers_sbo_kegg = obj_tables.StringAttribute(
        verbose_name='Identifiers:sbo.kegg')
    identifiers_kegg_compound = obj_tables.StringAttribute(
        verbose_name='Identifiers:kegg.compound')
    identifiers_obo_chebi = obj_tables.StringAttribute(
        verbose_name='Identifiers:obo.chebi')
    s_b_m_l_fbc_chemical_formula = obj_tables.StringAttribute(
        verbose_name='SBML:fbc:ChemicalFormula')
    s_b_m_l_fbc_charge = obj_tables.FloatAttribute(
        verbose_name='SBML:fbc:Charge')
    has_only_substance_units = obj_tables.BooleanAttribute(
        verbose_name='HasOnlySubstanceUnits')
    name_for_plots = obj_tables.StringAttribute(verbose_name='NameForPlots')

    class Meta(obj_tables.Model.Meta):
        table_format = obj_tables.TableFormat.row
        attribute_order = (
            'comment',
            'reference_name',
            'reference_pub_med',
            'reference_d_o_i',
            'description',
            'name',
            'miriam_annotations',
            'type',
            'symbol',
            'position_x',
            'position_y',
            'i_d',
            's_b_m_l_species_id',
            's_b_m_l_speciestype_id',
            'initial_value',
            'initial_concentration',
            'unit',
            'location',
            'state',
            'compound_sum_formula',
            'structure_formula',
            'charge',
            'mass',
            'is_constant',
            'enzyme_role',
            'regulator_role',
            's_b_o_term',
            'identifiers',
            'identifiers_sbo_kegg',
            'identifiers_kegg_compound',
            'identifiers_obo_chebi',
            's_b_m_l_fbc_chemical_formula',
            's_b_m_l_fbc_charge',
            'has_only_substance_units',
            'name_for_plots',
        )
        verbose_name = 'Compound'
        verbose_name_plural = 'Compound'