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 kcat 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
  • Welcome to the PAMparametrizer
  • View page source

Welcome to the PAMparametrizer

The PAModelpy package is designed to integrate protein constraints and protein sectors into protein allocation models (PAMs). In this documentation, you can find all the information you need to parametrizer PAMs.

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?
    • 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
    • Example 2: Parametrizing the E. coli Protein Allocation Model with multiple carbon sources
  • Workflow for Protein Allocation Model Parameter Estimation
    • Software Structure
    • PAM parametrizer workflow
    • Data objects
  • Parametrizing a PAM: from GEM to PAM
    • 1. The Genome-Scale Metabolic Model Sanity Check
    • 2. Building the Protein Sectors
    • 3. Design Choices
    • 4. Working with the PAMparametrizer
    • 5. Analyzing the Paramaterization Results
  • API reference
    • PAM_parametrizer
    • genetic_algorithm_parametrization
    • utils
Next

© Copyright 2026, iAMB, RWTH Aachen University.

Built with Sphinx using a theme provided by Read the Docs.