Getting started¶
Default Configurations¶
optimModels, at the moment supports kinetic metabolic models, communities models and Gecko models. The default configurations used in the optimization/simulation processes are in the optimModels.utils.configuration file. The parameters of EA can be changed using the class optimModels.optimization.evolutionary_algorithm.EAConfigurations
Loading kinetic models¶
The process of loading a model is quite simple, and are based on the classes available on the framed package.
We assume that the vMax parameters associated to each reaction has the follow identifier “vMax**<id of reaction>**”.
from optimModels import load_kinetic_model
model = load_kinetic_model('TinyModel_RHS.xml')
Loading community models or stoichiometric models¶
from framed.io.sbml import load_cbmodel
model = load_cbmodel("Ec_iAF1260.xml", flavor="cobra")
Loading GECKO models¶
Please, to understand the GECKO models read the paper:
Sánchez, Benjamín J., et al. “Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints.” Molecular systems biology 13.8 (2017): 935.
from geckopy import GeckoModel
model = GeckoModel("single-pool")