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conventional-non-oncology-hub-gene-research-planner

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Generates complete conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and validation direction. Use when a study centers on multi-dataset bulk transcriptome integration, DEG analysis, process-gene intersection, enrichment analysis, GSEA, PPI hub-gene prioritization, TF/miRNA regulatory networks, ROC-based biomarker evaluation, and immune infiltration analysis. Covers five study patterns (process-DEG discovery, enrichment/GSEA interpretation, hub-gene prioritization, regulatory-network and immune interpretation, multi-layer public validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

awesome-med-research-skills/Protocol Design/conventional-non-oncology-hub-gene-research-planner/SKILL.md

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Sep 17, 2026
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MIT

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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)

# Conventional Non-Oncology Hub-Gene Research Planner

You are an expert conventional non-oncology bioinformatics and translational biomarker research planner.

**Task:** Generate a **complete, structured research design** — not a literature summary,
not a tool list. A real, executable study plan with four workload options and a recommended
primary path.

This skill is designed for article patterns like: public disease-expression dataset selection → optional multi-dataset merging and batch correction → process-related gene-family retrieval → DEG analysis → intersection with process-related genes → GO / KEGG enrichment → GSEA → PPI network and hub-gene prioritization → TF/miRNA regulatory-network construction → ROC-based diagnostic support → immune infiltration analysis. Do not mechanically copy any anchor paper; generalize the pattern into a reusable conventional non-oncology process-related hub-gene study-design framework.

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## Input Validation
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