Systems Biology

Version Compatibility

Reference examples assume recent stable releases of the preferred tools, especially cobrapy and the other tools listed below.

Before using code or command patterns, verify installed versions match the environment:

• Python: python -c "import <module>; print(<module>.__version__)"
• CLI: <tool> --version
• If signatures differ, inspect the installed help or API and adapt the pattern instead of retrying unchanged.

Overview

Workflow for constraint-based metabolic modeling, context-specific models, gene essentiality, and systems-level interpretation.

When To Use This Skill

• use when the task is flux balance analysis, metabolic reconstruction, or model-based systems biology
• use when transcriptomic or metabolomic data must be folded into pathway or network models
• use when the user needs model-derived pathway behavior rather than only enrichment analysis

Quick Route

• If the input is raw or minimally processed data, start with validation and QC before any modeling.
• If the input is already processed, skip directly to the first workflow step that matches the user goal.
• If the user asks for a biological conclusion, always produce at least one QC or confidence artifact alongside the final result.

Progressive Disclosure

• Read references/technical_reference.md when you need deeper tool-selection rules, environment adaptation notes, or extra validation guidance.
• Keep SKILL.md as the main execution path and load the reference file only when the task or failure mode needs the extra detail.

Default Rules

• Prefer Python-first workflows unless the task explicitly requires something else.
• Keep intermediate and final outputs separated.
• Record software versions, reference builds, and key parameters when they affect interpretation.
• Favor reproducible tables and figures over one-off interactive-only outputs.

Expected Inputs

• metabolic model
• omics-derived constraints
• reaction and metabolite annotations

Expected Outputs

• flux solutions
• context-specific models
• pathway or essentiality summaries

Preferred Tools

• cobrapy
• pandas
• network utilities

Starter Pattern

import cobra

model = cobra.io.read_sbml_model("model.xml")
solution = model.optimize()
print(solution.objective_value)

Workflow

1. Validate the model

Check model format, reaction constraints, and biomass assumptions before analysis.

2. Integrate context

Incorporate condition- or tissue-specific evidence when the task calls for it.

3. Run systems analysis

Perform flux analysis, essentiality testing, or pathway-level model interrogation.

4. Interpret model outputs

Relate flux shifts or essential reactions back to the biological question.

5. Export model-derived summaries

Save flux tables, condition comparisons, and pathway views.

Output Artifacts

• Recommended output layout:
• results/ for final tables and serialized objects
• figures/ for plots and static visual exports
• qc/ for checks that justify downstream interpretation
• Minimum expected outputs for this skill:
• flux solutions
• context-specific models
• pathway or essentiality summaries

Quality Review

• Confirm identifiers and metadata join correctly before modeling or summarizing.
• Generate at least one QC artifact before final biological interpretation.
• Keep raw or minimally processed inputs separate from transformed outputs.
• Verify that modalities, samples, and model assumptions align before integration or inference.
• Export factors, scores, or model outputs together with interpretation context.

Anti-Patterns

• treating model predictions as direct measurements
• skipping feasibility checks before comparing conditions
• mixing curated and auto-generated models without documenting it

Related Skills

• Multi-Omics Integration
• Pathway Analysis
• Causal Genomics
• Machine Learning For Omics

Optional Supplements

• cobrapy