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cobrapy

Perform constraint-based metabolic simulations on genome-scale models with cobrapy.

7|Updated Apr 5, 2026
Search Tags:#cobrapy#metabolic-modeling#sbml#flux-sampling#flux-balance-analysis#flux-variability-analysis#gapfilling
One-click install
npx skills add https://github.com/dailycafi/metabolism-skills --skill cobrapy-dailycafi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cobrapy
Source: https://github.com/dailycafi/metabolism-skills/tree/main/skills/metabolic-modeling/cobrapy
Command: npx skills add https://github.com/dailycafi/metabolism-skills --skill cobrapy-dailycafi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

COBRApy streamlines constraint-based metabolic modeling so researchers can predict growth rates, evaluate pathway usage, and test genetic or environmental interventions without manual model tinkering.

Core Features & Use Cases

  • Model management and I/O: load and save SBML, JSON, and YAML genome-scale models.
  • Flux simulations: run flux balance analysis (FBA), parsimonious and geometric FBA, and change objectives.
  • Uncertainty and breadth analysis: flux variability analysis (FVA), loopless FVA, and flux sampling (OptGP, ACHR).
  • Perturbation screens: single/double gene and reaction deletions, knockout screens, and production strain design.
  • Media and production analysis: minimal media computation, production envelopes, and gapfilling with universal models.
  • Use case: screen all single-gene knockouts to identify essential genes and generate a ranked list of candidates for strain engineering.

Quick Start

Load the ecoli model and run flux balance analysis to report the growth rate and list fluxes with magnitude greater than 1e-6.

Frequently Asked Questions about cobrapy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform flux balance analysis on a genome-scale metabolic model?▼

Flux balance analysis predicts metabolic fluxes by optimizing an objective function in a genome-scale model. This Skill runs FBA on SBML, JSON, or YAML models and reports objective values and flux distributions for systems biology workflows.

Can I identify essential genes using single and double knockout screens?▼

You can identify essential genes by running single and double gene deletion screens. The Skill performs perturbation screens on metabolic models to evaluate knockout effects and generate ranked candidate lists for production strain design.

Does this tool support loading and saving SBML metabolic models?▼

Yes, it supports loading and saving SBML, JSON, and YAML genome-scale metabolic models. Model management and I/O are built-in, allowing you to import standard formats for constraint-based simulations without manual conversion.

What is flux variability analysis and when do I need it for metabolic engineering?▼

Flux variability analysis calculates the feasible range of each metabolic flux under given constraints. You need FVA for uncertainty and breadth analysis when evaluating pathway usage flexibility, supported here with standard and loopless implementations.

How do I find missing reactions in a metabolic model using gapfilling?▼

Gapfilling identifies missing reactions by comparing your model against a universal model to find candidates that restore network functionality. This Skill performs gapfilling to suggest reactions needed to complete metabolic pathways.

What is the difference between OptGP and ACHR flux sampling methods?▼

OptGP and ACHR are flux sampling algorithms for exploring the solution space of metabolic models. This Skill supports configurable parallel sampling using either method to generate ensembles characterizing possible metabolic phenotypes.

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