Analyze constraint-based metabolic models with COBRApy for flux and knockout predictions.
npx skills add https://github.com/dralkh/seerai --skill cobrapy-dralkh
Please help me install this Agent Skill. Skill: cobrapy Source: https://github.com/dralkh/seerai/tree/main/skills/cobrapy Command: npx skills add https://github.com/dralkh/seerai --skill cobrapy-dralkh
This Skill helps researchers analyze constraint-based metabolic models without manually writing repetitive analysis code. It speeds up growth prediction, flux exploration, knockout studies, and media design for systems biology and metabolic engineering projects.
Ask the AI to load a COBRApy metabolic model, run flux balance analysis, and summarize the growth rate and key reaction fluxes.
High-intent search queries and answers about installing and using this skill.
You can perform flux balance analysis on an SBML metabolic model by loading the file into the COBRApy workflow and running solver-backed optimization to predict growth rates and reaction fluxes. This Skill automates that entire process to summarize key metabolic behavior.
Flux variability analysis calculates the range of possible flux values for each reaction in a constraint-based metabolic model. You need it for metabolic engineering when identifying alternative pathways and evaluating production envelopes to find strain optimization targets.
Yes, you can simulate gene knockout effects on microbial growth by applying gene-reaction rules within a constraint-based model. This Skill screens essential genes and predicts resulting growth rates to identify viable production strain engineering targets.
Yes, this flux analysis workflow supports loading and exporting SBML, JSON, YAML, and MATLAB metabolic model formats. You can open existing constraint-based models or save curated versions for reuse in downstream systems biology research.
Minimal media design and gap filling are performed by analyzing model consistency and identifying missing reactions in the metabolic network. This Skill automates these COBRApy validation workflows to ensure your constraint-based model supports the desired growth conditions.
The best way to compare aerobic versus anaerobic growth predictions is to run flux balance analysis under different environmental constraints. This Skill manages the COBRApy simulations to contrast growth rates and flux distributions across varying media conditions.
jaechang-hitsPerform COBRA analyses of genome-scale metabolic models with Python.
dailycafiPredict growth rates and flux distributions for genome-scale models with COBRApy.
Estrella-231Optimize fluxes in genome-scale metabolic models with COBRApy.
jimmc414Simulate metabolic networks and analyze fluxes with COBRApy.
