cobrapy
Analyze Metabolic Models with COBRApy
Complex metabolic analyses require correct model setup and suitable optimization methods. This skill provides practical COBRApy guidance for reproducible analysis and validation.
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Review the Skillstore skill "cobrapy" from https://skillstore.io/skills/davila7-cobrapy.md and its manifest at https://skillstore.io/api/skills/davila7-cobrapy/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
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Test it
Using "cobrapy". Assess baseline growth and flux flexibility for the E. coli core model.
Expected outcome:
The model is feasible with an optimal growth objective. FVA identifies fixed reactions, flexible reactions, and ranges requiring biological interpretation.
Using "cobrapy". Find candidate gene knockouts that improve acetate production while preserving growth.
Expected outcome:
The analysis ranks viable knockouts by production gain and retained growth. It also records infeasible cases and recommends validation with combined deletions.
Using "cobrapy". Validate an imported SBML model before simulation.
Expected outcome:
The report covers feasibility, mass balance, dead-end metabolites, duplicate reactions, orphan genes, and thermodynamically infeasible loops.
Security Audit
SafeAll 71 static findings are false positives caused by Python imports, Markdown code fences, COBRA model identifiers, and a documentation link. No command execution, dynamic loading, credential access, system reconnaissance, prompt injection, or malicious intent was found.
Risk Factors
⚡ Contains scripts (4)
⚙️ External commands (50)
🌐 Network access (1)
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APA citation
davila7. (2026). cobrapy security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-cobrapy/audits/9BibTeX citation
@techreport{davila7-davila7-cobrapy-2026,
author = {davila7},
title = {cobrapy security audit report (audit version 9)},
institution = {Skillstore},
year = {2026},
number = {9},
url = {https://skillstore.io/skills/davila7-cobrapy/audits/9},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "cobrapy security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
- name: "davila7"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/davila7-cobrapy/audits/9"
identifiers:
- type: other
value: "skillstore:davila7-cobrapy:audit:9"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
k-dense-ai-cobrapy
2026-08-21
davila7-cobrapy
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Evaluate a Metabolic Model
Load an SBML model, verify feasibility, inspect components, and summarize baseline growth and active fluxes.
Screen Engineering Targets
Compare gene knockouts, production envelopes, and flux changes to prioritize strain engineering candidates.
Teach Constraint-Based Analysis
Create structured examples for FBA, FVA, model constraints, gene rules, and growth media.
Try These Prompts
Load the COBRApy model [model name or file]. Report its objective, dimensions, medium, solver status, and baseline objective value.
Analyze [model] with FBA and FVA at [fraction] optimality. Compare objective value, reaction ranges, and potentially flexible pathways.
Plan a knockout study for [model] under [medium]. Define thresholds, screen genes or reactions, and summarize essential and beneficial targets.
Evaluate production of [target metabolite] from [carbon source]. Combine growth constraints, production envelopes, knockout screening, FVA, and model validation.
Best Practices
- Use model context managers for temporary changes so the original model remains unchanged.
- Check solver status and model feasibility before interpreting objective values or fluxes.
- Record model version, medium, objective, solver, bounds, and analysis parameters for reproducibility.
Avoid
- Do not interpret one optimal flux distribution as the only biologically possible state.
- Do not modify reaction bounds or media without documenting units and biological assumptions.
- Do not treat computational knockout predictions as experimental validation.
Frequently Asked Questions
What model formats are supported?
Does this skill install COBRApy?
Can it perform flux balance analysis?
Can it identify essential genes?
How should uncertain fluxes be assessed?
Are predictions experimentally validated?
Developer Details
Author
davila7License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Ref
c43861a65bb95efcae259cd161c9d6f4dc7eec6f
Maintenance freshness
7/24/2026
Usage
5 downloads · 207 views
File structure