2. pyTFA models¶
pyTFA models are based on COBRApy models
, with
additional values.
2.1. Compartment data¶
This is the compartments
attribute of the model. It is a dict
where
each key is the symbol of a compartment, and the value is another dict
with the following keys :
c_min |
|
c_max |
|
ionicStr |
|
membranePot |
Each key is the symbol of another compartment (which is the destination compartment), and the value is the potential (in mV) from the source to the destination. |
name |
|
pH |
|
symbol |
|
Here is an example:
cobra_model.compartments['c'] = {
'c_max': 0.01,
'c_min': 9.9999999999999995e-08,
'ionicStr': 0.25,
'membranePot': {
'c': 0,
'e': 60,
'g': 0,
'm': -180,
'n': 0,
'p': 0,
'r': 0,
't': 0,
'v': 0,
'x': 0
},
'name': 'Cytosol',
'pH': 7.0,
'symbol': 'c'
}
2.2. Metabolites¶
Each metabolite must be annotated with its SeedID
, which will be used to get
the thermodynamic values from the Thermodynamic Databases. In order to do this, use the
annotation
attribute of each
metabolite
. Here is an example:
cobra_model.metabolites[0].annotation = {
'SeedID': 'cpd00018'
}
pyTFA will also define a thermo
a thermo attribute for each metabolite,
which is a pytfa.thermo.MetaboliteThermo
.
2.3. Reactions¶
pyTFA will define a thermo
attribute for each reaction. It is a
dict
with the following attributes:
computed |
|
deltaGR |
If the thermodynamic values were not computed, this is
|
deltaGRerr |
If the thermodynamic values were not computed, this is
|
deltaGrxn |
|
isTrans |
|
Here are some examples:
cobra_model.reactions[0].thermo = {
'computed': False,
'deltaGR': 10000000,
'deltaGRerr': 10000000,
'isTrans': False
}
cobra_model.reactions[99].thermo = {
'computed': True,
'deltaGR': 1.161097833014658,
'deltaGRerr': 2,
'deltaGrxn': 0,
'isTrans': True,
}