reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters

SimulationData mass data

class reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters.GrowthRateParameters(raw_data, sim_data)[source]

Bases: object

_fit_ribosome_elongation_rate_by_ppgpp(ppgpp, rate)[source]
get_fraction_active_ribosome(doubling_time)[source]
get_fraction_active_rnap(doubling_time)[source]
get_ppGpp_conc(doubling_time)[source]
get_ribosome_elongation_rate(doubling_time)[source]
get_ribosome_elongation_rate_by_ppgpp(ppgpp, max_rate=None)[source]
get_rnap_elongation_rate(doubling_time)[source]
class reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters.Mass(raw_data, sim_data)[source]

Bases: object

_build_CD_periods(raw_data, sim_data)[source]
_build_constants(raw_data, sim_data)[source]
_build_dependent_constants()[source]
_build_submasses(raw_data, sim_data)[source]
_build_trna_data(raw_data, sim_data)[source]
_calculateGrowthRateDependentDnaMass(doubling_time)[source]
_clipTau_d(doubling_time)[source]
_getFitParameters(dry_mass_composition, mass_fraction_name)[source]
getBiomassAsConcentrations(doubling_time, rp_ratio=None)[source]
get_avg_cell_dry_mass(doubling_time)[source]

Gets the dry mass for an average cell at the given doubling time.

Parameters:

doubling_time (Unum) – expected doubling time

Returns:

average cell dry mass

Return type:

Unum

get_basal_rna_fractions()[source]

Measured RNA subgroup mass fractions. Fractions should change in other conditions with growth rate (see transcription.get_rna_fractions()).

get_component_masses(doubling_time)[source]
get_dna_critical_mass(doubling_time)[source]

Returns the critical mass for replication initiation. Faster growing cells maintain a consistent initiation mass but slower growing cells are smaller and will never reach this mass so it needs to be adjusted lower for them.

Parameters:

doubling_time (Unum) – expected doubling time of cell

Returns:

Critical mass for DNA replication initiation

Return type:

Unum

get_mass_fractions(doubling_time)[source]
get_mass_fractions_from_rna_protein_ratio(ratio)[source]
get_trna_distribution(doubling_time)[source]
reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters._get_fit_parameters(list_of_dicts, key)[source]
reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters._get_linearized_fit(x, y, **kwargs)[source]
reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters._loadRow(key, list_of_dicts)[source]
reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters._loadTableIntoObjectGivenDoublingTime(obj, list_of_dicts)[source]
reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters._useFitParameters(x_new, function, x_units, y_units, dtype)[source]
reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters._use_linearized_fit(x, params)[source]
reconstruction.ecoli.dataclasses.growth_rate_dependent_parameters.linear_regression(x, y, r_tol=0.999, p_tol=1e-05)[source]

Perform linear regression on a data set and check that statistics are within expected values to confirm a good linear fit.

Parameters:

  • x (ndarray[Any, dtype[float64]]) – x values for regression

  • y (ndarray[Any, dtype[float64]]) – y values for regression

  • r_tol (float) – lower limit for r statistic

  • p_tol (float) – upper limit for p statistic

Returns:

2-element tuple containing

  • slope: linear fit slope

  • intercept: linear fit intercept

Return type:

tuple[float, float]