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cobrapy

Perform constraint-based metabolic modeling with FBA, FVA, and flux sampling.

21|2|Updated Dec 8, 2025
Search Tags:#metabolic modeling#gene knockout#flux balance analysis#constraint-based modeling#flux sampling#flux variability analysis#SBML
One-click install
npx skills add https://github.com/silverstein/claude-scientific-skills-desktop --skill cobrapy-silverstein
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cobrapy
Source: https://github.com/silverstein/claude-scientific-skills-desktop/tree/main/corpus/cobrapy
Command: npx skills add https://github.com/silverstein/claude-scientific-skills-desktop --skill cobrapy-silverstein

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

COBRApy helps you predict and analyze cellular metabolism by turning genome-scale metabolic knowledge into constraint-based models that can be optimized and tested under different assumptions.

Core Features & Use Cases

  • Load and convert metabolic models: Import SBML/JSON/YAML models, and save results back to exchangeable formats for reuse and sharing.
  • Run simulation workflows: Perform Flux Balance Analysis (FBA), parsimonious/ geometric FBA, and quickly extract objective values and reaction fluxes.
  • Characterize system behavior: Compute Flux Variability Analysis (FVA), sample feasible flux distributions, and quantify production envelopes for strain/design questions.
  • Test perturbations and feasibility: Evaluate gene/reaction knockouts, run gapfilling to repair incomplete networks, and build models from scratch for new hypotheses.
  • Use Case: Given an E. coli genome-scale model, compute baseline growth with FBA, then run an FVA at 90% optimality to identify reactions with the widest allowable flux ranges.

Quick Start

Ask the AI to load the bundled E. coli model, run FBA to report the objective value, then run FVA at 90% optimality and summarize the widest flux-ranging reactions.

Frequently Asked Questions about cobrapy

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

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

Flux balance analysis computes optimized phenotypes and flux distributions by loading a COBRApy model object with solver-based optimization capability, then executing FBA to extract objective values and reaction fluxes.

Can I import SBML metabolic models for constraint-based modeling?▼

SBML metabolic models can be imported for constraint-based modeling, alongside JSON and YAML formats, allowing you to load reconstruction networks and save results back to exchangeable formats for reuse and sharing.

How do I evaluate gene knockout effects on metabolic flux distributions?▼

Gene knockout effects on metabolic flux distributions are evaluated by testing perturbations and feasibility on a loaded COBRApy model, running gene or reaction deletion studies to predict resulting cellular phenotypes.

What is the best way to identify reactions with the widest allowable flux ranges?▼

Identifying reactions with the widest allowable flux ranges requires running Flux Variability Analysis (FVA) at a specified optimality threshold, characterizing system behavior by quantifying feasible flux bounds across the network.

Does constraint-based modeling support flux sampling and production envelope calculations?▼

Constraint-based modeling supports flux sampling to sample feasible flux distributions and production envelope calculations to quantify strain design parameters, alongside gapfilling to repair incomplete metabolic networks.

Why does my metabolic model require solver-based optimization for FBA simulations?▼

FBA simulations require solver-based optimization because constraint-based modeling mathematically optimizes objective values under defined network constraints, necessitating a COBRApy model object configured with an underlying linear programming solver.

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