PhilippStaedter/sedml_import

Assessment and Prediction of ODE Solver Performance for Biological Processes

It follows the order in which all scripts are executed.

1 Create model collection

1.1 Download all sedml and sbml models from the JWS Online Database

script_download_all_sedml_models.py

1.2 Download chosen sbml models from the BioModels Database

downloaded "by hand" --- no script available

1.3 Import all sbml models to AMICI

sbml2amici.py
sbml2amici_BioModelsDatabase.py

1.4 Check for correctly generated .so files and delete all other sbml models

no explicit script yet 

1.5 Compare the state trajectories of the local simulation to the in-built simulation routine of JWS

compareStateTrajectories_1.py
compareStateTrajectories_2.py
compareStateTrajectories_plot.py

1.6 Derive the whole model collection

correctStateTrajectories.py

1.7 Plot basic properties

plot_first_results.py
stat_reac_par.py
Intern_vs_Extern.py
num_x_num_p.py

2 Solver settings study

2.1 Tolerance study

execute_Tolerances.py
plotHistogram.py
plotBoxPlot.py

2.2 Linear solver study

execute_LinearSolvers.py
plotScatter.py

2.3 Non-linear solver study

execute_NonlinearSolvers.py
(no plotting script yet)

2.4 Multistep method study

execute_SolAlg.py
plotScatter2.py
plotScatter3.py

3 Predictor model

3.1 Get the input data (by determination of the kinetic rate law) for the logistic regression

Input_Data.py

3.2 Predictor model with/without cross-validation

Predictor.py
PredictorCV.py
PredictorCV_2.py

3.3 Divide all categorical Input values into more sections

DivComb.py 

3.4 Plot different results

plotAdamsBDF.py
plotAdBf.py
plotPrediction.py