Can I use this skill for gene knockout studies?

Yes, the skill provides specific patterns for performing single and double gene/reaction deletions to observe growth impacts and identify essential genes.

What is COBRApy used for?

COBRApy is a Python library designed for constraint-based reconstruction and analysis (COBRA) of metabolic models, essential for systems biology and metabolic engineering.

Does it support SBML models?

Absolutely, it supports reading and writing models in SBML (the industry standard), as well as JSON and YAML formats.

What types of flux analysis are supported?

It supports standard Flux Balance Analysis (FBA), parsimonious FBA (pFBA), geometric FBA, and Flux Variability Analysis (FVA) to determine flux ranges.

COBRApy Scientific Modeling

Name: COBRApy Scientific Modeling
Author: K-Dense-AI

byK-Dense-AI

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3,717

Ciencia de Datos y ML

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

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This skill integrates COBRApy's powerful metabolic modeling capabilities into Claude, enabling researchers and bioinformaticians to perform Flux Balance Analysis (FBA), Flux Variability Analysis (FVA), and gene knockout simulations. It simplifies the management of genome-scale metabolic models (GEMs), allowing users to load SBML files, modify growth media, calculate minimal media, and sample flux distributions. Ideal for metabolic engineering and systems biology workflows, it provides a structured approach to predicting cellular phenotypes and identifying essential genes for industrial or medical research.

Características Principales

Model management and I/O for SBML, JSON, and YAML formats
Flux Variability Analysis (FVA) and flux sampling for uncertainty quantification
Gene and reaction knockout simulations to identify essential metabolic pathways
Advanced metabolic engineering tools including production envelopes and gapfilling
Constraint-based metabolic reconstruction and Flux Balance Analysis (FBA)
3,717 GitHub stars

Casos de Uso

Predicting bacterial growth rates and phenotypic behavior under different nutrient conditions
Identifying metabolic targets and knockout strategies for bio-industrial strain engineering
Analyzing metabolic flux distributions and steady-state behavior in genome-scale models

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Características Principales

Model management and I/O for SBML, JSON, and YAML formats
Flux Variability Analysis (FVA) and flux sampling for uncertainty quantification
Gene and reaction knockout simulations to identify essential metabolic pathways
Advanced metabolic engineering tools including production envelopes and gapfilling
Constraint-based metabolic reconstruction and Flux Balance Analysis (FBA)
3,717 GitHub stars

Casos de Uso

Predicting bacterial growth rates and phenotypic behavior under different nutrient conditions
Identifying metabolic targets and knockout strategies for bio-industrial strain engineering
Analyzing metabolic flux distributions and steady-state behavior in genome-scale models