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
- Identifies the analysis type from the user's input (enrichment, drug, comparison, network)
- Resolves identifiers — maps gene symbols, drug names, or pathway IDs to KEGG entries
- Retrieves cross-linked data — follows relationships across KEGG databases
- Aggregates and ranks results — counts pathway hits, scores conservation, groups by function
- 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:
search_genes for each gene in the target organism (e.g., hsa)
get_gene_info to confirm identity and get KEGG gene IDs
find_related_entries to get pathway associations per gene
- Aggregate: count how many input genes map to each pathway
get_pathway_info for top pathways
render_pathway_ascii for visual context
- Report ranked pathways with p-value proxy (gene count / pathway size)
Drug Target Investigation
Investigate metformin: targets, pathways, and interactions
Workflow:
search_drugs to find the KEGG drug entry
get_drug_info for targets, classification, and metabolism
search_genes for each target gene
find_related_entries to get target pathways
get_drug_interactions for DDI screening
- Synthesize mechanism-of-action summary
Cross-Species Comparison
Compare glycolysis (map00010) between human, E. coli, and yeast
Workflow:
get_pathway_info for organism-specific variants (hsa00010, eco00010, sce00010)
get_pathway_genes for each organism
get_gene_orthologs to identify conserved vs. species-specific enzymes
get_pathway_compounds to compare metabolite pools
render_pathway_ascii for each organism
- 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
Source: davepoon/buildwithclaude → plugins/kegg-mcp-server/skills/kegg-analysis/SKILL.md
1---2name: kegg-analysis3description: Multi-step KEGG bioinformatics workflows — pathway enrichment from gene lists, drug-target investigation, cross-species metabolic comparison, and compound-reaction network exploration. Guides Claude through the full analytical pipeline using KEGG MCP tools.4---5
6
7# KEGG Bioinformatics Analysis
8
9This 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.
10
11## When to Use This Skill
12
13- Performing pathway enrichment analysis on a gene list
14- Investigating a drug's mechanism of action, targets, and interactions
15- Comparing metabolic pathways across species
16- Tracing compound-reaction networks
17- Mapping genes to functional modules and ortholog groups
18
19## What This Skill Does
20
211. **Identifies the analysis type** from the user's input (enrichment, drug, comparison, network)
222. **Resolves identifiers** — maps gene symbols, drug names, or pathway IDs to KEGG entries
233. **Retrieves cross-linked data** — follows relationships across KEGG databases
244. **Aggregates and ranks results** — counts pathway hits, scores conservation, groups by function
255. **Synthesizes biological context** — explains significance, not just IDs
26
27## How to Use
28
29### Pathway Enrichment
30
31```
32Analyze these genes for pathway enrichment in human: BRCA1, TP53, EGFR, KRAS, PIK3CA
33```
34
35Workflow:
361. `search_genes` for each gene in the target organism (e.g., hsa)
372. `get_gene_info` to confirm identity and get KEGG gene IDs
383. `find_related_entries` to get pathway associations per gene
394. Aggregate: count how many input genes map to each pathway
405. `get_pathway_info` for top pathways
416. `render_pathway_ascii` for visual context
427. Report ranked pathways with p-value proxy (gene count / pathway size)
43
44### Drug Target Investigation
45
46```
47Investigate metformin: targets, pathways, and interactions
48```
49
50Workflow:
511. `search_drugs` to find the KEGG drug entry
522. `get_drug_info` for targets, classification, and metabolism
533. `search_genes` for each target gene
544. `find_related_entries` to get target pathways
555. `get_drug_interactions` for DDI screening
566. Synthesize mechanism-of-action summary
57
58### Cross-Species Comparison
59
60```
61Compare glycolysis (map00010) between human, E. coli, and yeast
62```
63
64Workflow:
651. `get_pathway_info` for organism-specific variants (hsa00010, eco00010, sce00010)
662. `get_pathway_genes` for each organism
673. `get_gene_orthologs` to identify conserved vs. species-specific enzymes
684. `get_pathway_compounds` to compare metabolite pools
695. `render_pathway_ascii` for each organism
706. Report conservation matrix and unique adaptations
71
72## Example
73
74**User**: "What pathways are enriched in this gene set: SOD1, SOD2, CAT, GPX1, PRDX1?"
75
76**Output**:
77```
78Pathway Enrichment Results (Homo sapiens)
79
80Top Pathways:
811. hsa04146 Peroxisome (4/5 genes) — organelle for fatty acid oxidation and ROS detox
822. hsa04216 Ferroptosis (3/5 genes) — iron-dependent cell death regulated by GPX
833. hsa05022 Pathways of neurodegeneration (3/5 genes) — oxidative damage in ALS, AD, PD
844. hsa00480 Glutathione metabolism (2/5 genes) — GSH-dependent antioxidant system
85
86Biological Context:
87All 5 genes encode antioxidant enzymes. The enrichment in Peroxisome
88and Ferroptosis pathways reflects their central role in reactive oxygen
89species (ROS) detoxification. The neurodegeneration hit is consistent
90with oxidative stress as a driver of SOD1-linked ALS.
91```
92
93## Tips
94
95- Provide organism context (human, mouse, E. coli) for faster resolution
96- Use standard gene symbols — KEGG resolves HGNC symbols for human
97- For large gene lists (>20), batch with `batch_entry_lookup` (max 50 per call)
98- Cross-reference with `convert_identifiers` to bridge UniProt, NCBI Gene, or PDB IDs
99- Use `find_related_entries` to discover unexpected connections between databases
100
101---
102
103**Source:** [`davepoon/buildwithclaude`](https://github.com/davepoon/buildwithclaude) → `plugins/kegg-mcp-server/skills/kegg-analysis/SKILL.md`