Perform flux balance analysis on genome-scale metabolic models with cobrapy.
npx skills add https://github.com/tassiovale/claude-code-kit --skill cobrapy-tassiovale
Please help me install this Agent Skill. Skill: cobrapy Source: https://github.com/tassiovale/claude-code-kit/tree/main/skills/cobrapy Command: npx skills add https://github.com/tassiovale/claude-code-kit --skill cobrapy-tassiovale
This Skill simplifies constraint-based metabolic modeling (COBRA) for systems biology and metabolic engineering analysis, allowing users to perform complex simulations and analyses efficiently.
Use the cobrapy skill to load the bundled model 'textbook' and perform a flux balance analysis (FBA) to predict growth rate.
High-intent search queries and answers about installing and using this skill.
Flux balance analysis (FBA) on genome-scale metabolic models is performed by loading a model and running computational simulations to predict cellular growth rates and phenotypic behavior. The cobrapy skill facilitates this using the glpk solver.
Simulating genetic knockouts to study effects on cellular metabolism is supported through gene and reaction deletion studies. This allows you to perform knockout analyses and observe the resulting predictive phenotypic behavior modifications.
Designing and optimizing growth media for a specific metabolic pathway involves configuring minimal media inputs to maximize cellular growth or the production of a target metabolite. This Skill enables direct growth media design and optimization simulations.
Constraint-based metabolic modeling with COBRA requires Python 3.9 or higher. The environment must include specific libraries like cobra, optlang, and glpk to ensure the solvers function correctly for computational simulations.
Flux variability analysis (FVA) works with genome-scale metabolic models to determine the range of possible flux values. This Skill enables FVA alongside FBA and flux sampling to analyze cellular metabolism constraints.
Loading and saving constraint-based metabolic models is handled through built-in model management features that support various formats. You can load bundled models like the 'textbook' example or save modified genome-scale models directly.
galeepAnalyze and simulate metabolic models with flux balance analysis using COBRApy.
TurnaboutHeroPerform ML modeling, causal inference, and time-series analysis with scikit-learn and statsmodels.
tondevrelSolve combinatorial optimization problems with Google OR-Tools and CP-SAT.
Lord1EgyptPerform constraint-based metabolic model analysis with FBA, FVA, and gene knockout workflows.
