# 15.1.1.2.1.6. cobra.flux_analysis.parsimonious¶

## 15.1.1.2.1.6.1. Module Contents¶

cobra.flux_analysis.parsimonious.optimize_minimal_flux(*args, **kwargs)[source]
cobra.flux_analysis.parsimonious.pfba(model, fraction_of_optimum=1.0, objective=None, reactions=None)[source]

Perform basic pFBA (parsimonious Enzyme Usage Flux Balance Analysis) to minimize total flux.

pFBA [1] adds the minimization of all fluxes the the objective of the model. This approach is motivated by the idea that high fluxes have a higher enzyme turn-over and that since producing enzymes is costly, the cell will try to minimize overall flux while still maximizing the original objective function, e.g. the growth rate.

Parameters: model (cobra.Model) – The model fraction_of_optimum (float, optional) – Fraction of optimum which must be maintained. The original objective reaction is constrained to be greater than maximal_value * fraction_of_optimum. objective (dict or model.problem.Objective) – A desired objective to use during optimization in addition to the pFBA objective. Dictionaries (reaction as key, coefficient as value) can be used for linear objectives. reactions (iterable) – List of reactions or reaction identifiers. Implies return_frame to be true. Only return fluxes for the given reactions. Faster than fetching all fluxes if only a few are needed. The solution object to the optimized model with pFBA constraints added. cobra.Solution

References

 [1] Lewis, N. E., Hixson, K. K., Conrad, T. M., Lerman, J. A., Charusanti, P., Polpitiya, A. D., Palsson, B. O. (2010). Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models. Molecular Systems Biology, 6, 390. doi:10.1038/msb.2010.47
cobra.flux_analysis.parsimonious.add_pfba(model, objective=None, fraction_of_optimum=1.0)[source]