17.1.1.2.1.2. cobra.flux_analysis.fastcc

Provide an implementation of FASTCC.

17.1.1.2.1.2.1. Module Contents

17.1.1.2.1.2.1.1. Functions

_find_sparse_mode(model, rxns, flux_threshold, zero_cutoff)

Perform the LP required for FASTCC.

_flip_coefficients(model, rxns)

Flip the coefficients for optimizing in reverse direction.

fastcc(model, flux_threshold=1.0, zero_cutoff=None)

Check consistency of a metabolic network using FASTCC 1.

cobra.flux_analysis.fastcc._find_sparse_mode(model, rxns, flux_threshold, zero_cutoff)[source]

Perform the LP required for FASTCC.

Parameters
  • model (cobra.core.Model) – The cobra model to perform FASTCC on.

  • rxns (list of cobra.core.Reactions) – The reactions to use for LP.

  • flux_threshold (float) – The upper threshold an auxiliary variable can have.

  • zero_cutoff (float) – The cutoff below which flux is considered zero.

Returns

result – The list of reactions to consider as consistent.

Return type

list

cobra.flux_analysis.fastcc._flip_coefficients(model, rxns)[source]

Flip the coefficients for optimizing in reverse direction.

cobra.flux_analysis.fastcc.fastcc(model, flux_threshold=1.0, zero_cutoff=None)[source]

Check consistency of a metabolic network using FASTCC 1.

FASTCC (Fast Consistency Check) is an algorithm for rapid and efficient consistency check in metabolic networks. FASTCC is a pure LP implementation and is low on computation resource demand. FASTCC also circumvents the problem associated with reversible reactions for the purpose. Given a global model, it will generate a consistent global model i.e., remove blocked reactions. For more details on FASTCC, please check 1.

Parameters
  • model (cobra.Model) – The constraint-based model to operate on.

  • flux_threshold (float, optional (default 1.0)) – The flux threshold to consider.

  • zero_cutoff (float, optional) – The cutoff to consider for zero flux (default model.tolerance).

Returns

The consistent constraint-based model.

Return type

cobra.Model

Notes

The LP used for FASTCC is like so: maximize: sum_{i in J} z_i s.t. : z_i in [0, varepsilon] forall i in J, z_i in mathbb{R}_+

v_i ge z_i forall i in J Sv = 0 v in B

References

1(1,2,3)

Vlassis N, Pacheco MP, Sauter T (2014) Fast Reconstruction of Compact Context-Specific Metabolic Network Models. PLoS Comput Biol 10(1): e1003424. doi:10.1371/journal.pcbi.1003424