ecoli.processes.metabolism_redux_classic

MetabolismRedux

class ecoli.processes.metabolism_redux_classic.FlowResult(velocities, dm_dt, exchanges, objective)[source]

Bases: object

Reaction velocities and dm/dt for an FBA solution, with metrics.

Parameters:
dm_dt: Iterable[float]
exchanges: Iterable[float]
objective: float
velocities: Iterable[float]
class ecoli.processes.metabolism_redux_classic.MetabolismReduxClassic(parameters)[source]

Bases: Step

concentrationToCounts(concs)[source]
defaults: Dict[str, Any]
{   'catalyst_ids': [],
    'cell_density': 1100.0 [g/L],
    'concentration_updates': None,
    'kinetic_rates': [],
    'maintenance_reaction': {},
    'media_id': 'minimal',
    'objective_type': 'homeostatic',
    'reaction_catalysts': [],
    'stoichiometry': []}
getBiomassAsConcentrations(doubling_time)[source]

Caches the result of the sim_data function to improve performance since function requires computation but won’t change for a given doubling_time.

Parameters:

doubling_time (Unum) – doubling time of the cell to get the metabolite concentrations for

Returns:

Mapping from metabolite IDs to concentration targets

name = 'ecoli-metabolism-redux-classic'
next_update(timestep, states)[source]
ports_schema()[source]
topology
{   'boundary': ('boundary',),
    'bulk': ('bulk',),
    'bulk_total': ('bulk',),
    'environment': {'_path': ('environment',), 'exchange': ('exchange',)},
    'global_time': ('global_time',),
    'listeners': ('listeners',),
    'next_update_time': ('next_update_time', 'metabolism'),
    'polypeptide_elongation': ('process_state', 'polypeptide_elongation'),
    'timestep': ('timestep',)}
update_condition(timestep, states)[source]

See update_condition().

class ecoli.processes.metabolism_redux_classic.NetworkFlowModel(stoich_arr, metabolites, reactions, homeostatic_metabolites, kinetic_reactions, free_reactions=None)[source]

Bases: object

A network flow model for estimating fluxes in the metabolic network based on network structure. Flow is mainly driven by precursor demand (homeostatic objective) and availability of nutrients.

Parameters:
set_up_exchanges(exchanges, uptakes)[source]

Set up exchange reactions for the network flow model. Exchanges allow certain metabolites to have flow out of the system. Uptakes allow certain metabolites to also have flow into the system.

Parameters:
solve(homeostatic_targets=None, maintenance_target=0, kinetic_targets=None, binary_kinetic_idx=None, objective_weights=None, upper_flux_bound=100, solver=cvxpy.GLOP)[source]

Solve the network flow model for fluxes and dm/dt values.

Parameters:
Return type:

FlowResult