class DerivativeGroup(BiologicalModel):
name = dmodels.CharField(max_length=600,
unique=True,
di_show=True,
di_display_name='derivative_group')
def __str__(self):
return self.name
class Pathway(MetaModel):
name = dmodels.CharField(max_length=255,
unique=True,
di_show=True,
di_display_name='pathway')
reaction = dmodels.ManyToManyField('Reaction', related_name='reactions')
def __str__(self):
return self.name
class Locus(BiologicalModel):
di_first = True
locus_tag = dmodels.CharField(max_length=255, unique=True, di_show=True)
product = dmodels.CharField(max_length=255, di_show=True, blank=True)
ec_number = ArrayField(dmodels.CharField(max_length=15,
blank=True,
validators=[ec_validator]),
blank=True,
verbose_name='EC number')
reaction = dmodels.ManyToManyField('Reaction', related_name='loci')
class Meta:
verbose_name_plural = "loci"
def __str__(self):
try:
return '{} -- {}'.format(self.locus_tag, self.gene.product)
except:
return '{}'.format(self.locus_tag)
class CoADerivative(BiologicalModel):
name = dmodels.CharField(max_length=600,
unique=True,
di_show=True,
di_display_name='CoA_derivative')
class Meta:
verbose_name_plural = 'CoA derivatives'
def __str__(self):
return self.name
class Metabolite(BiologicalModel):
name = dmodels.CharField(max_length=512,
di_display_name='metabolite_name',
di_show=True)
derivative_group = dmodels.ForeignKey('DerivativeGroup',
null=True,
blank=True)
co_a_derivative = dmodels.ForeignKey('CoADerivative',
null=True,
blank=True)
def __str__(self):
return self.name
class Reaction(BiologicalModel):
name = dmodels.CharField(max_length=255,
unique=True,
di_show=True,
di_display_name='reaction_name')
reaction_equation = dmodels.TextField()
lb = dmodels.FloatField(null=True, blank=True)
ub = dmodels.FloatField(null=True, blank=True)
brenda = dmodels.CharField(max_length=13, blank=True)
kegg = dmodels.CharField(max_length=10, blank=True, di_show=True)
metacyc = dmodels.CharField(max_length=100, blank=True)
pubmed = dmodels.CharField(max_length=12, blank=True)
notes = dmodels.TextField(blank=True)
metabolite = dmodels.ManyToManyField(
'Metabolite',
related_name='reactions') #, through='ReactionMetabolite')
def __str__(self):
"""Return equation and database ID if exists in specified order."""
allowed_length = 30
if self.brenda:
return self.brenda
elif self.metacyc:
return self.metacyc
elif self.kegg:
return self.kegg
else:
if len(self.reaction_equation) < allowed_length:
return self.reaction_equation
else:
return self.reaction_equation[:30] + '[...]'
@property
def brendalink(self):
if self.brenda:
prefix = self.brenda[:2]
refid = self.brenda[2:]
link = '<a href="http://www.brenda-enzymes.org/structure.php?show=reaction&id={}&type={}&displayType=marvin">{}</a>'
if prefix == 'BS':
return format_html(link, mark_safe(refid), mark_safe('S'),
self.brenda)
elif prefix == 'BR':
return format_html(link, mark_safe(refid), mark_safe('I'),
self.brenda)
else:
return None
@property
def kegglink(self):
if self.kegg:
link = '<a href="http://www.genome.jp/dbget-bin/www_bget?rn:{}">{}</a>'
return format_html(link, mark_safe(self.kegg), self.kegg)
else:
return None
@property
def metacyclink(self):
if self.metacyc:
link = '<a href="http://metacyc.org/META/NEW-IMAGE?type=NIL&object={}&redirect=T">{}</a>'
return format_html(link, mark_safe(self.metacyc), self.metacyc)
else:
return None
@property
def db_crossref(self):
return (self.brendalink or self.kegglink or self.metacyclink
or 'No cross reference found.')
@property
def short_reaction(self):
allowed_length = 30
if len(self.reaction_id < allowed_length):
return self.reaction_id
else:
return self.reaction_id[:30] + '[...]'
class Experiment(models.Model, DisbiExperiment):
EXPERIMENT_TYPE_CHOICES = (
('transcriptome', 'Transcriptome'),
('proteome', 'Proteome'),
('metabolome', 'Metabolome'),
('flux', 'Predicted Flux'),
)
experiment_type = dmodels.CharField(max_length=45,
choices=EXPERIMENT_TYPE_CHOICES,
di_choose=True)
# The first name is the DB name, the second is human readable.
EXPERIMENT_METHOD_CHOICES = (
('Transcriptome', (('rnaseq', 'RNAseq'), )),
('Proteome', (('shotgun', 'shotgun'), )),
('Metabolome', (
('gcms', 'GCMS'),
('coa', 'CoA-method'),
)),
('Predicted Flux', (('fba', 'FBA'), )),
)
experiment_method = dmodels.CharField(max_length=45,
choices=EXPERIMENT_METHOD_CHOICES,
di_choose=True)
c_source = dmodels.CharField(max_length=45,
blank=True,
verbose_name='Carbon source',
di_choose=True,
di_show=True,
di_combinable=True)
place = dmodels.CharField(max_length=45)
group = dmodels.CharField(max_length=45)
raw_data = dmodels.ForeignKey(
'RawData', help_text='A file with the raw data for the experiment')
notes = dmodels.TextField(blank=True, default='')
class Meta:
unique_together = (('experiment_type', 'experiment_method', 'c_source',
'group', 'raw_data'), )
def __str__(self):
return '{}. {}: {}'.format(
self.id,
self.get_experiment_type_display(),
self.get_experiment_method_display(),
)
def clean(self):
"""
Check whether the experiment method matches the experiment type.
"""
opt_groups = get_optgroups(self.EXPERIMENT_METHOD_CHOICES)
hr_experiment_type = get_hr_val(self.EXPERIMENT_TYPE_CHOICES,
self.experiment_type)
if self.experiment_method not in opt_groups[hr_experiment_type]:
hr_experiment_method = get_hr_val(
remove_optgroups(self.EXPERIMENT_METHOD_CHOICES),
self.experiment_method)
raise ValidationError(
_('{type} does not belong to the method {method}.'.format(
type=hr_experiment_type, method=hr_experiment_method)))
def c_source_display(self):
return self.c_source if self.c_source else '-'
c_source_display.short_description = 'Carbon source'