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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.

When to use

• 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

When not to use

• clinical treatment recommendations
• patient-specific diagnosis
• prescribing
• pure oncology studies with tumor-specific survival-model or pan-cancer logic
• pure single-cell-only studies with no bulk discovery backbone
• pure wet-lab mechanistic studies with no bioinformatics integration
• non-biomedical / off-topic requests

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