PAMparametrizer
1.0.0
Table of Contents
PAMparametrizer - parametrizing Protein Allocation Models with Flux Data
Why do we need a PAMparametrizer?
What does the PAMparametrizer do?
What can you find where in this repository?
PAMparametrizer functionality
Code structure
Dependencies
License
Genetic Algorithm for Protein Allocation Model Parameter Estimation
Software Structure
Genetic Algorithm workflow
Fitness Evaluation adjustment
Example usage of the PAMparametrizer
Example 1: Parametrizing the
E. coli
Protein Allocation Model with glucose as sole carbon source
Step 0: Initiate the sectors
Step 0.1 Initialize the active enzyme parameter set using GotEnzymes
Step 0.1 The Translational Protein Sector
Step 0.2 The Unused Enzyme Sector
Step 1: Organize the data
Step 2: Build the Protein Allocation Model
Step 3: Create the data objects required for the PAMparametrizer
i. Parse the sector configuration
ii. Get the ValidationData
iii. Define the HyperParameters
iv. ParametrizationResults and FluxResults
Step 4: Build the PAMparametrizer object
Step 5: Run!
Step 6: Analyze the Results
Example 2: Parametrizing the
E. coli
Protein Allocation Model with multiple carbon sources
Step 0: Initiate the sectors
Step 1: Organize the data
Step 2: Build the PAM
Step 3: Create the data objects required for the PAMparametrizer
i. Parse the sector configuration
i. Get the ValidationData
ii. Define the HyperParameters
Step 4: Build the PAMparametrizer object
Step 5: Run!
Step 6: Analyze the Results
Workflow for Protein Allocation Model Parameter Estimation
Software Structure
PAM parametrizer workflow
Data objects
SectorConfig
ValidationData
HyperParameters
ParametrizationResults
FluxResults
Parametrizing a PAM: from GEM to PAM
1. The Genome-Scale Metabolic Model Sanity Check
2. Building the Protein Sectors
2.1 Initiating the ActiveEnzymesSector
2.2 Parametrizing the TranslationalProteinSector
2.3 Parametrizing the UnusedEnzymesSector
3. Design Choices
3.1 Total protein content
3.2 Scaling kcat values
3.3 Which conditions?
3.4 Getting the validation data
4. Working with the PAMparametrizer
4.1 Building and running the PAMparametrizer
4.2 Creating an ensemble of models
5. Analyzing the Paramaterization Results
5.1 The output
5.1.1 Best_Individuals
5.1.2 Computational_time
5.1.3 Final_Errors
5.1.4 sector_parameters
5.1.5 reaction_weights
5.2 Prebuilt analyses
5.2.1 k
cat
distribution
5.2.2 Flux prediction accuracy
5.2.3 Protein Prediction accuracy
API reference
PAM_parametrizer
PAMparametrizer.PAM_parametrizer.KcatConstraintConfig
PAMparametrizer.PAM_parametrizer.PAM_data_classes
PAMparametrizer.PAM_parametrizer.pam_parametrizer
PAMparametrizer.PAM_parametrizer
genetic_algorithm_parametrization
PAMparametrizer.genetic_algorithm_parametrization.Evaluation.Fitfun_params_gaussian
PAMparametrizer.genetic_algorithm_parametrization.Evaluation.Fitfun_params_uniform
PAMparametrizer.genetic_algorithm_parametrization.Evaluation
PAMparametrizer.genetic_algorithm_parametrization.core_parametrization_gaussian
PAMparametrizer.genetic_algorithm_parametrization.core_parametrization_uniform
PAMparametrizer.genetic_algorithm_parametrization.ga_param
PAMparametrizer.genetic_algorithm_parametrization
utils
PAMparametrizer.utils.error_calculation
PAMparametrizer.utils.genetic_algorithm_analysis
PAMparametrizer.utils.pam_generation
PAMparametrizer.utils.pamparametrizer_analysis
PAMparametrizer.utils.pamparametrizer_setup
PAMparametrizer.utils.pamparametrizer_visualization
PAMparametrizer.utils.preprocessing
PAMparametrizer.utils.sampling_functions
PAMparametrizer.utils.sector_config_functions
PAMparametrizer.utils
PAMparametrizer
API reference
PAM_parametrizer
PAMparametrizer.PAM_parametrizer.PAM_data_classes
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