Can I import existing SBML models with this skill?

Yes, the skill supports reading and writing models in standard formats including SBML (.xml), JSON, and YAML.

Does it support gene knockout simulations?

Absolutely. You can perform single and double gene or reaction deletions to observe the impact on the objective function, such as biomass production.

Is flux sampling supported for large models?

Yes, it includes advanced sampling methods like OptGP and ACHR to explore the feasible flux space of genome-scale models.

How does it handle temporary model modifications?

It utilizes Python context managers, allowing you to make temporary changes to bounds or objectives that automatically revert once the analysis is complete.

What is the primary use of the COBRApy skill?

The COBRApy skill is used for constraint-based modeling of metabolic networks, allowing users to simulate cellular metabolism and predict growth rates or metabolic fluxes.

COBRApy Metabolic Modeling

Name: COBRApy Metabolic Modeling
Author: ricable

byricable

•

Ciencia de Datos y ML

Performs constraint-based metabolic modeling and analysis for systems biology and metabolic engineering using the COBRApy library.

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COBRApy is a specialized skill that enables Claude to perform comprehensive constraint-based reconstruction and analysis (COBRA) of metabolic models. It facilitates complex simulations of cellular metabolism, including Flux Balance Analysis (FBA), Flux Variability Analysis (FVA), and gene knockout studies. This tool is essential for researchers and bioengineers working with genome-scale metabolic models to predict phenotypic behaviors, optimize growth media, and design metabolic pathways for industrial applications.

Características Principales

Conducts Flux Variability Analysis (FVA) to determine feasible flux ranges
Calculates production envelopes and samples feasible flux spaces
Performs Flux Balance Analysis (FBA) and Parsimonious FBA (pFBA)
Executes single and double gene/reaction knockout simulations
Manages metabolic models in SBML, JSON, and YAML formats
1 GitHub stars

Casos de Uso

Predicting microbial growth rates and phenotype changes under varying nutrient conditions
Identifying essential genes for drug discovery and metabolic engineering targets
Optimizing industrial production pathways by analyzing carbon yield and metabolic flux

Acerca de

Características Principales

Conducts Flux Variability Analysis (FVA) to determine feasible flux ranges
Calculates production envelopes and samples feasible flux spaces
Performs Flux Balance Analysis (FBA) and Parsimonious FBA (pFBA)
Executes single and double gene/reaction knockout simulations
Manages metabolic models in SBML, JSON, and YAML formats
1 GitHub stars

Casos de Uso

Predicting microbial growth rates and phenotype changes under varying nutrient conditions
Identifying essential genes for drug discovery and metabolic engineering targets
Optimizing industrial production pathways by analyzing carbon yield and metabolic flux