Individual skill
dual-disease-transcriptomic-ml-planner
Generates complete dual-disease transcriptomic + machine learning research designs from a user-provided disease pair. Use when users want to identify shared DEGs, common hub genes, cross-disease biomarkers, or shared molecular mechanisms between two diseases using public GEO data. Triggers:"shared biomarker study for two diseases", "dual-disease transcriptomic ML paper", "identify common DEGs between disease A and B", "cross-disease hub gene discovery", "shared DEG + PPI + ROC design", "immune infiltration shared biomarker", or "I want to study disease X and Y together". Always outputs four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, and publication upgrade path.
scientific-skills/Protocol Design/dual-disease-transcriptomic-ml-planner/SKILL.md
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- Last checked
- Nov 9, 2026
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- Sep 17, 2026
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- bioinformatics Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- ai Repository topic
- biology Repository topic
- cancer-genomics Repository topic
- data-visualization Repository topic
- differential-expression Repository topic
- genomics Repository topic
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- research Derived category
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SKILL.mdcore · 15,060 byteseval_report_dual-disease-transcriptomic-ml-planner_polished_result.jsonasset · 15,791 bytesreferences/figure_plan_template.mddoc · 3,146 bytesreferences/geo_search_and_tools.mddoc · 5,782 bytesreferences/tissue_and_tool_decisions.mddoc · 5,635 bytesreferences/upgrade_path.mddoc · 3,702 bytes
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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# Dual-Disease Transcriptomic Machine Learning Research Planner
Generates a complete dual-disease transcriptomic + ML study design from a user-provided disease pair. Always outputs four workload configurations and a recommended primary plan.
## Supported Study Styles
| Style | Description | Example |
|-------|-------------|---------|
| **A. Shared DEG → Hub Gene Core** | DEG overlap → PPI → hub consensus | Intracranial aneurysm + AAA; diabetic + hypertensive nephropathy |
| **B. Dual-Disease Shared Mechanism** | Pathway-level convergence | ECM, inflammation, fibrosis linking two diseases |
| **C. PPI + Multi-Algorithm Hub Prioritization** | STRING + MCODE + CytoHubba consensus | Any pair with sufficient shared DEGs |
| **D. Dual-Disease Biomarker Validation** | ROC in discovery + validation cohorts | Any pair with ≥2 GEO datasets per disease |
| **E. Immune Infiltration + Shared Biomarker** | CIBERSORT/alternative + gene–immune correlation | Immunologically active disease pairs |