What is the difference between FBA and FVA in this context?

FBA finds a single optimal solution for a metabolic objective, while FVA determines the full range of possible fluxes for each reaction while maintaining that optimality.

Can Claude perform gene knockout simulations with this skill?

Yes, Claude can perform single and double gene or reaction deletions to predict growth impact and identify essential genes.

What model formats does this COBRApy skill support?

The skill supports standard metabolic modeling formats including SBML (preferred), JSON (for Escher compatibility), and YAML.

Does it support flux sampling for large models?

Yes, it includes patterns for sampling the feasible flux space using methods like OptGP and ACHR, including parallel processing support.

How do I manage temporary changes to a metabolic model?

The skill emphasizes using Python context managers, allowing you to make temporary modifications to bounds or objectives that automatically revert.

COBRApy Metabolic Modeling

Name: COBRApy Metabolic Modeling
Author: sanand0

bysanand0

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Ciencia de Datos y ML

Performs constraint-based metabolic modeling, flux balance analysis, and gene knockout simulations for systems biology and metabolic engineering.

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COBRApy is a specialized skill that empowers Claude to reconstruct and analyze genome-scale metabolic models using the Python COBRApy library. It enables sophisticated systems biology workflows, including Flux Balance Analysis (FBA), Flux Variability Analysis (FVA), and phenotypic predictions. Whether you are identifying essential genes through knockout studies, optimizing growth media, or sampling flux distributions, this skill provides the domain-specific guidance and implementation patterns required to navigate complex metabolic networks and biological datasets efficiently.

Características Principales

Flux Balance Analysis (FBA) and Parsimonious FBA (pFBA) simulations
Comprehensive gene and reaction deletion studies
Flux Variability Analysis (FVA) for determining metabolic ranges
Model management for SBML, JSON, and YAML formats
Growth media optimization and minimal media calculations
3 GitHub stars

Casos de Uso

Performing systematic gene knockout screens to identify essential biological components.
Predicting bacterial growth rates and metabolic fluxes under various environmental constraints.
Designing metabolic engineering strategies to maximize the production of target metabolites.

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Características Principales

Flux Balance Analysis (FBA) and Parsimonious FBA (pFBA) simulations
Comprehensive gene and reaction deletion studies
Flux Variability Analysis (FVA) for determining metabolic ranges
Model management for SBML, JSON, and YAML formats
Growth media optimization and minimal media calculations
3 GitHub stars

Casos de Uso

Performing systematic gene knockout screens to identify essential biological components.
Predicting bacterial growth rates and metabolic fluxes under various environmental constraints.
Designing metabolic engineering strategies to maximize the production of target metabolites.