Can I perform gene knockout simulations using this skill?

Yes, it provides comprehensive tools for single and double gene/reaction deletions, helping you identify essential genes and predict growth phenotypes after mutations.

What model formats are supported by the COBRApy skill?

The skill supports standard metabolic modeling formats including SBML (Systems Biology Markup Language), JSON, and YAML, ensuring compatibility with major model repositories like BiGG.

Can I use this to optimize growth media?

Yes, you can calculate minimal media requirements and modify exchange reactions to simulate different nutrient environments and optimize growth conditions.

Does it support Flux Variability Analysis (FVA)?

Absolutely. The skill includes functions for standard FVA, loopless FVA to eliminate infeasible cycles, and FVA at specific optimality thresholds.

COBRApy Metabolic Modeling

Name: COBRApy Metabolic Modeling
Author: Microck

byMicrock

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Data Science & ML

Performs constraint-based reconstruction and analysis of metabolic models using Python for systems biology and metabolic engineering.

About

COBRApy is a specialized skill designed for researchers and bioinformaticians to simulate and analyze cellular metabolism within the Claude environment. It enables advanced computational operations such as Flux Balance Analysis (FBA), Flux Variability Analysis (FVA), and gene knockout simulations on genome-scale metabolic models. By streamlining the management of SBML models and the optimization of growth conditions, this skill helps users predict phenotypic behaviors and identify essential genes, making it an indispensable tool for computational biology and metabolic engineering workflows.

Key Features

Constraint-based metabolic simulations including FBA, FVA, and pFBA
Automated gene and reaction deletion studies for knockout analysis
Growth media optimization and minimal media requirement calculations
Advanced flux sampling and production envelope generation for pathway analysis
81 GitHub stars
Genome-scale model management for SBML, JSON, and YAML formats

Use Cases

Predicting microbial growth rates and metabolic fluxes under varying environmental conditions
Identifying essential genes and metabolic bottlenecks for industrial strain engineering
Analyzing the metabolic impact of specific gene deletions or enzymatic inhibitions

About

Key Features

Constraint-based metabolic simulations including FBA, FVA, and pFBA
Automated gene and reaction deletion studies for knockout analysis
Growth media optimization and minimal media requirement calculations
Advanced flux sampling and production envelope generation for pathway analysis
81 GitHub stars
Genome-scale model management for SBML, JSON, and YAML formats

Use Cases

Predicting microbial growth rates and metabolic fluxes under varying environmental conditions
Identifying essential genes and metabolic bottlenecks for industrial strain engineering
Analyzing the metabolic impact of specific gene deletions or enzymatic inhibitions