bio-systems-biology-flux-balance-analysis

Version Compatibility

Reference examples tested with: COBRApy 0.29+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Flux Balance Analysis

"Predict growth rate and metabolic fluxes for my organism" → Solve a linear program over a genome-scale metabolic model to find the optimal flux distribution that maximizes biomass (or a custom objective), and assess flux ranges with FVA.

• Python: model.optimize(), cobra.flux_analysis.flux_variability_analysis() (COBRApy)

Load Models

import cobra

# Load built-in test models
model = cobra.io.load_model('textbook')  # E. coli core (95 reactions)
model = cobra.io.load_model('iJO1366')   # Full E. coli (2583 reactions)

# Load from file
model = cobra.io.read_sbml_model('model.xml')
model = cobra.io.load_json_model('model.json')

# BiGG models available at: http://bigg.ucsd.edu/models

Basic FBA

Goal: Predict optimal metabolic flux distributions and growth rates for an organism under defined conditions.

Approach: Load a genome-scale metabolic model, solve the linear program to maximize the biomass objective function, then inspect flux values and solver status to interpret metabolic phenotype.

import cobra

model = cobra.io.load_model('textbook')

# Run FBA (maximizes objective function, usually biomass)
solution = model.optimize()

# Growth rate interpretation:
# >0.8 h^-1: Fast growth (rich media)
# 0.3-0.8 h^-1: Moderate growth
# <0.3 h^-1: Slow growth or stress
# 0: No growth (lethal condition or missing nutrients)
print(f'Growth rate: {solution.objective_value:.4f} h^-1')
print(f'Status: {solution.status}')

# Access flux values
for rxn in model.reactions[:5]:
    print(f'{rxn.id}: {solution.fluxes[rxn.id]:.4f}')