COBRApy Constraint Based Metabolic Modeling
Skill AktivConstraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. Part of the AlterLab Academic Skills suite.
To empower researchers in systems biology and metabolic engineering with advanced tools for analyzing and simulating cellular metabolism using constraint-based models.
Funktionen
- Constraint-based metabolic modeling (COBRA)
- Flux Balance Analysis (FBA) and FVA
- Gene knockout and deletion studies
- Flux sampling and production envelope analysis
- Model loading, saving, and manipulation
Anwendungsfälle
- Analyzing metabolic pathways and flux distributions in biological systems.
- Predicting the phenotypic effects of gene knockouts or modifications.
- Designing strains for metabolic engineering and bioproduction.
- Exploring the feasible flux space of metabolic networks.
Nicht-Ziele
- Performing dynamic metabolic modeling (time-dependent simulations).
- Directly simulating gene expression or protein levels.
- Providing a graphical user interface for model building.
- Replacing the need for underlying COBRApy library installation.
Workflow
- Load a metabolic model (SBML, JSON, YAML, or bundled).
- Perform Flux Balance Analysis (FBA) to determine optimal flux.
- Conduct Flux Variability Analysis (FVA) to assess flux ranges.
- Execute gene or reaction deletion studies (knockouts).
- Utilize flux sampling for exploring feasible flux space.
- Design production strains and optimize media conditions.
Praktiken
- Model validation
- Metabolic engineering
- Systems biology analysis
- Computational biology
Voraussetzungen
- Python 3.7+
- COBRApy library installed (`pip install cobra`)
Maintenance
- warning:Dependency ManagementThe project uses external Python libraries but lacks explicit dependency pinning mechanisms like a lockfile (e.g., requirements.txt, Pipfile.lock), increasing the risk of incompatible versions.
Trust
- info:Issues AttentionThere are 2 open issues and 0 closed issues in the last 90 days, indicating low recent engagement or a new project.
Execution
- warning:Pinned dependenciesWhile Python scripts are used, they lack shebangs declaring the interpreter and side-effect headers, and specific dependency pinning is missing (as noted in Dependency Management).
Installation
npx skills add AlterLab-IEU/AlterLab-Academic-SkillsFührt das Vercel skills CLI (skills.sh) via npx aus — benötigt Node.js lokal und mindestens einen installierten skills-kompatiblen Agent (Claude Code, Cursor, Codex, …). Setzt voraus, dass das Repo dem agentskills.io-Format folgt.
Qualitätspunktzahl
Vertrauenssignale
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