FBA
Flux balance analysis
FBA task class
Performs Flux Balance Analysis from a digital twin.
A digital twin is a mathematical representation of the metabolic interactions involved in a living cell or microbial organism (e.g. animal cell, bacteria, fungus, etc.).
You need to provide your twin in the input and you can set some parameters. The most important is to choose whether you want to maximize or minimize the biomass flux. Then, you can add other fluxes to optimize (fluxes to maximize and fluxes to minimize), the solver and some parameters related to the solver method. The last parameter "Number of simulations" allows you to run multiple simulations of FBA using your context with multi target values.
In output you will get your twin annotated and two tables with the estimated fluxes.
Input
Output
Configuration
biomass_optimization
Biomass optimization
stringmaximize minimize fluxes_to_maximize
The fluxes to maximize
listfluxes_to_minimize
The fluxes to minimize
listsolver
The optimization solver. It is recommended to use `quad`. Other solvers are in `beta` versions.
stringquad highs-ds highs-ipm highs interior-point quadrelax_qssa
True to relaxing the quasi-steady state assumption (QSSA) constrain (`quad` solver is used). False otherwise.
boolqssa_relaxation_strength
Used only if the QSSA is relaxed. The higher is the strength, the stronger is the QSSA. Hint: Set to the number of reactions to have strong QSSA contrain.
floatparsimony_strength
Set True to perform parsimonious FBA (pFBA). In this case the quad solver is used. Set False otherwise
floatnumber_of_simulations
Set the number of simulations to perform. You must provide at least the same number of measures in the context. By default, keeps all simulations.
int