kegg-analysis

# KEGG Bioinformatics Analysis This skill orchestrates multi-step biological analyses using the KEGG MCP server tools. It transforms raw gene lists, drug names, or pathway IDs into structured biological insights. ## When to Use This Skill - Performing pathway enrichment analysis on a gene list - Investigating a drug's mechanism of action, targets, and interactions - Comparing metabolic pathways across species - Tracing compound-reaction networks - Mapping genes to functional modules and ortholog groups ## What This Skill Does 1. **Identifies the analysis type** from the user's input (enrichment, drug, comparison, network) 2. **Resolves identifiers** — maps gene symbols, drug names, or pathway IDs to KEGG entries 3. **Retrieves cross-linked data** — follows relationships across KEGG databases 4. **Aggregates and ranks results** — counts pathway hits, scores conservation, groups by function 5. **Synthesizes biological context** — explains significance, not just IDs ## How to Use ### Pathway Enrichment ``` Analyze these genes for pathway enrichment in human: BRCA1, TP53, EGFR, KRAS, PIK3CA ``` Workflow: 1. `search_genes` for each gene in the target organism (e.g., hsa) 2. `get_gene_info` to confirm identity and get KEGG gene IDs 3. `find_related_entries` to get pathway associations per gene 4. Aggregate: count how many input genes map to each pathway 5. `get_pathway_info` for top pathways 6. `render_pathway_ascii` for visual context 7. Report ranked pathways with p-value proxy (gene count / pathway size) ### Drug Target Investigation ``` Investigate metformin: targets, pathways, and interactions ``` Workflow: 1. `search_drugs` to find the KEGG drug entry 2. `get_drug_info` for targets, classification, and metabolism 3. `search_genes` for each target gene 4. `find_related_entries` to get target pathways 5. `get_drug_interactions` for DDI screening 6. Synthesize mechanism-of-action summary ### Cross-Species Comparison ``` Compare glycolysis (map00010) between human, E. coli, and yeast ``` Workflow: 1. `get_pathway_info` for organism-specific variants (hsa00010, eco00010, sce00010) 2. `get_pathway_genes` for each organism 3. `get_gene_orthologs` to identify conserved vs. species-specific enzymes 4. `get_pathway_compounds` to compare metabolite pools 5. `render_pathway_ascii` for each organism 6. Report conservation matrix and unique adaptations ## Example **User**: "What pathways are enriched in this gene set: SOD1, SOD2, CAT, GPX1, PRDX1?" **Output**: ``` Pathway Enrichment Results (Homo sapiens) Top Pathways: 1. hsa04146 Peroxisome (4/5 genes) — organelle for fatty acid oxidation and ROS detox 2. hsa04216 Ferroptosis (3/5 genes) — iron-dependent cell death regulated by GPX 3. hsa05022 Pathways of neurodegeneration (3/5 genes) — oxidative damage in ALS, AD, PD 4. hsa00480 Glutathione metabolism (2/5 genes) — GSH-dependent antioxidant system Biological Context: All 5 genes encode antioxidant enzymes. The enrichment in Peroxisome and Ferroptosis pathways reflects their central role in reactive oxygen species (ROS) detoxification. The neurodegeneration hit is consistent with oxidative stress as a driver of SOD1-linked ALS. ``` ## Tips - Provide organism context (human, mouse, E. coli) for faster resolution - Use standard gene symbols — KEGG resolves HGNC symbols for human - For large gene lists (>20), batch with `batch_entry_lookup` (max 50 per call) - Cross-reference with `convert_identifiers` to bridge UniProt, NCBI Gene, or PDB IDs - Use `find_related_entries` to discover unexpected connections between databases