Tutorial

The tutorial is composed of nine distinct Jupyter notebooks, which systematically guide the user through the workflows of creating, modifying, and optimizing various genome-scale extended models. These models are used as a case study to illustrate the principles and applications of genome-scale modeling. The latest FBA model of E. coli serves as a representative example throughout the tutorial.

jupyter notebooks

• 1. Tutorial: Create iML1515 GECKO
  • Prerequisites
  • Background
  • General
  • Other organisms
  • This Tutorial
  • Step 1: Initial Setup
  • Step 2: Create configuration files
  • Step 3: Create GECKO model
  • Step 4: Load and optimize GECKO model (cobrapy)
  • Step 5: Analyze results
  • (Optional) Track progress
  • Closing remarks
  • (Alternative) gurobipy - model optimization
  • References
• 2. Tutorial: Create iML1515 GECKO with modified default values
  • Step 1: Initial setup
  • Step 2: Export kcats values and enzyme composition
  • Step 3: Modify turnover numbers and enzyme composition
  • Step 4: Create XBA and ECM configuration files
  • Step 5: Create GECKO model
  • Step 4: Load and optimize GECKO model (cobrapy)
  • (Optional) Track progress
  • Closing remarks
  • (Alternative) gurobipy - model optimization
  • References
• 3. Tutorial: Create iML1515 GECKO model with predicted turnover numbers
  • Step 1: Initial setup
  • Step 2: Predict turnover values using TurNuP
  • Step 3: Create XBA and ECM configuration files
  • Step 4: Create GECKO model
  • Step 5: Load and optimize GECKO model (cobrapy)
  • (Optional) Track progress
  • Closing remarks
  • (alternatively) Load GECKO model, optimize and analyze (gurobipy)
  • References
• 4. Tutorial: Create iML1515 GECKO with manually adjusted turnover numbers
  • Step 1: Initial setup
  • Step 2: Analyze baseline GECKO model (cobrapy)
  • Step 3: Manual adjustment of model parameters
  • Step 4: Create GECKO model with adjusted parameters
  • Step 5: Load and optimize GECKO model (cobrapy)
  • (Optional) Track progress
  • Closing remarks
  • (Alternative) gurobipy - manual parameter fitting
  • References
• 5. Tutorial: Create iML1515 GECKO with auto-fitted turnover numbers
  • Step 1: Initial setup
  • Step 2: Fit turnover values to proteomics (cobrapy)
  • Step 3: Create GECKO model with fitted parameters
  • Step 4: Load and optimize GECKO model (cobrapy)
  • Step 5 – GECKO model limitations
  • (Optional) Track progress
  • Closing remarks
  • (Alternative) gurobipy – automatic fitting to proteomics data
  • References
• 6. Tutorial: Create iML1515 RBA model
  • RBA implementation details
  • Step 1: Initial setup
  • Step 2: Create XBA and RBA configuration files
  • Step 3: Create RBA model
  • Step 4. Load and optimize GECKO model (COBRApy)
  • (Optional) Track progress
  • Closing remarks
  • (Alternative) gurobipy - model optimization
  • References
• 7. Tutorial: Create iML1515 TFA model
  • Step 1: Initial setup
  • Step 2: Create XBA and preliminary TFA configuration files
  • Step 3: Create preliminary TFA model
  • Step 4: Model relaxation (cobrapy)
  • Step 5: Update TFA parameters and create final TFA model
  • Step 6. Load and optimize TFA model (cobrapy)
  • Closing remarks
  • (Alternative) gurobipy – TFA model creation
  • (Alternative) gurobipy – TFA model optimization
  • Implementation details
  • References
• 8. Tutorial: Create iML1515 TGECKO model
  • Step 1: Initial setup
  • Step 2: Create TGECKO model
  • Step 3. Load and optimize TGECKO model (COBRApy)
  • (Optional) Track progress
  • (Alternative) gurobipy - model optimization
• 9. Tutorial: Create iML1515 TRBA model
  • Step 1: Initial setup
  • Step 2: Create TRBA model
  • Step 3. Load and optimize TRBA model (COBRApy)
  • (Optional) Track progress
  • (Alternative) gurobipy - model optimization