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General models invent biology. We build the layer they check against — a curated knowledge graph, validated pipelines, and a provenance ledger, callable over MCP.
데이터Python · CypherGitHub @vkhangraphomics온라인운영자 미확인
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1분 만에 확인하기MicroMap: a microbiome knowledge graph platform (Neo4j) with MapForge, a reviewable BioCypher ingestion pipeline.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
Graphomics' microbiome knowledge graph platform, providing comprehensive access to microbiome-disease associations, taxonomic data, and metabolite relationships.
Not to be confused with the "MicroMap" microbiome-metabolism network
visualization resource from the Thiele lab (University of Galway), published
in npj Biofilms and Microbiomes
(2025) and hosted on Harvard Dataverse.
That project visualizes genome-scale metabolic reconstructions; this one is
a Neo4j-backed knowledge graph + ingestion platform. Unrelated projects,
same name, same field — no affiliation between them.README 전문 보기 ↗Graphomics' microbiome knowledge graph platform, providing comprehensive access to microbiome-disease associations, taxonomic data, and metabolite relationships.
Not to be confused with the "MicroMap" microbiome-metabolism network visualization resource from the Thiele lab (University of Galway), published in npj Biofilms and Microbiomes (2025) and hosted on Harvard Dataverse. That project visualizes genome-scale metabolic reconstructions; this one is a Neo4j-backed knowledge graph + ingestion platform. Unrelated projects, same name, same field — no affiliation between them.
Clone and configure:
cp .env.example .env
# Edit .env with your settings
Start the services:
docker compose up -d
Load data:
# Load all data sources
docker compose exec micromap-api python -m database.load_knowledge_graph --all
# Or load specific sources
docker compose exec micromap-api python -m database.load_knowledge_graph --taxonomy
docker compose exec micromap-api python -m database.load_knowledge_graph --disbiome
Access the API:
All /api/v1/* endpoints require an API key. Include your key in the X-API-Key header:
curl -H "X-API-Key: your-api-key" http://localhost:8200/api/v1/stats
Rate limit: 100 requests per minute per API key.
For full API documentation, see the Graphomics docs.
| Endpoint | Description |
|---|---|
GET /health | Health check (no auth required) |
GET /api/v1/stats | Knowledge graph statistics |
| Endpoint | Description |
|---|---|
GET /api/v1/search?q=query | Full-text search across all entity types |
GET /api/v1/search/suggest?q=query | Autocomplete suggestions |
GET /api/v1/search/counts?q=query | Match counts by entity type |
| Endpoint | Description |
|---|---|
GET /api/v1/taxa | List taxa (filter by rank, kingdom, name) |
GET /api/v1/taxa/{id} | Get taxon details |
GET /api/v1/taxa/{id}/children | Child taxa in hierarchy |
GET /api/v1/taxa/{id}/diseases | Associated diseases |
GET /api/v1/taxa/{id}/metabolites | Produced metabolites |
GET /api/v1/taxa/{id}/lineage | Full taxonomic lineage |
GET /api/v1/taxa/search/{query} | Search taxa by name |
GET /api/v1/taxa/compare?ids=... | Compare metabolite production across taxa |
| Endpoint | Description |
|---|---|
GET /api/v1/diseases | List all diseases with taxa counts |
GET /api/v1/diseases/{id} | Disease details with top associated taxa |
GET /api/v1/diseases/{id}/taxa | All taxa associated with a disease |
GET /api/v1/diseases/{id}/related | Diseases with similar microbiome profiles |
GET /api/v1/diseases/{id}/metabolites | Metabolites linked via producing taxa |
GET /api/v1/diseases/compare?ids=... | Compare microbiome profiles between diseases |
| Endpoint | Description |
|---|---|
GET /api/v1/metabolites | List metabolites (filter by name, category) |
GET /api/v1/metabolites/{id} | Metabolite details |
GET /api/v1/metabolites/{id}/producers | Taxa that produce this metabolite |
GET /api/v1/metabolites/{id}/diseases | Diseases linked via producing taxa |
GET /api/v1/metabolites/{id}/pathways | Pathways this metabolite participates in |
GET /api/v1/metabolites/categories/list | Metabolite categories with counts |
| Endpoint | Description |
|---|---|
GET /api/v1/drugs | List drugs |
GET /api/v1/drugs/{id} | Drug details |
GET /api/v1/drugs/{id}/taxa | Taxa that metabolize/interact with a drug |
GET /api/v1/drugs/{id}/diseases | Disease connections via microbiome |
GET /api/v1/drugs/search/{query} | Search drugs by name |
| Endpoint | Description |
|---|---|
GET /api/v1/genes | List genes |
GET /api/v1/genes/{id} | Gene details |
GET /api/v1/genes/{id}/taxa | Taxa with this gene |
GET /api/v1/genes/{id}/pathways | Pathways this gene participates in |
GET /api/v1/genes/search/{query} | Search genes by name |
| Endpoint | Description |
|---|---|
GET /api/v1/proteins | List proteins |
GET /api/v1/proteins/{id} | Protein details |
GET /api/v1/proteins/{id}/drugs | Drugs targeting this protein |
| Endpoint | Description |
|---|---|
GET /api/v1/pathways | List pathways with metabolite counts |
GET /api/v1/pathways/{id} | Pathway details |
GET /api/v1/pathways/{id}/metabolites | Metabolites in this pathway |
GET /api/v1/pathways/{id}/genes | Genes in this pathway |
GET /api/v1/pathways/{id}/taxa | Taxa linked via metabolites or genes |
GET /api/v1/pathways/search/{query} | Search pathways by name |
| Endpoint | Description |
|---|---|
GET /api/v1/biomarkers | List biomarker signatures |
GET /api/v1/biomarkers/{id} | Signature details with features and metrics |
GET /api/v1/biomarkers/disease/{id} | Best signatures for a disease |
| Endpoint | Description |
|---|---|
GET /api/v1/papers | List papers (filter by year, title) |
GET /api/v1/papers/{pmid} | Paper details with mentioned entities |
GET /api/v1/papers/taxon/{id} | Papers mentioning a taxon |
GET /api/v1/papers/disease/{id} | Papers related to a disease |
GET /api/v1/papers/search/{query} | Search papers by title/abstract |
| Endpoint | Description |
|---|---|
GET /api/v1/networks/cross-feeding | Cross-feeding network between taxa |
GET /api/v1/networks/cross-feeding/{id} | Cross-feeding partners for a taxon |
| Endpoint | Description |
|---|---|
GET /api/v1/discovery/probiotics/{disease_id} | Probiotic candidates for a disease |
GET /api/v1/discovery/scfa-producers | SCFA-producing taxa |
| Endpoint | Description |
|---|---|
GET /api/v1/provenance/sources | Data sources with entity counts |
GET /api/v1/provenance/entity/{id} | Provenance for a specific entity |
GET /api/v1/provenance/stats | Coverage metrics by label |
| Endpoint | Description |
|---|---|
GET /api/v1/graph/path | Shortest path between two entities |
GET /api/v1/graph/connections | All shortest paths between two entities |
GET /api/v1/graph/neighborhood | Entities within N hops of a given entity |
Set these environment variables in your application:
NEO4J_URI=bolt://your-micromap-server:7687
NEO4J_USER=neo4j
NEO4J_PASSWORD=your-password
Or use the REST API:
import requests
response = requests.get("http://your-micromap-server:8200/api/v1/diseases/diabetes/taxa")
taxa = response.json()["taxa"]
| Source | Description | Key Stats |
|---|---|---|
| NCBI Taxonomy | Microbial taxonomy hierarchy | 1,101,289 taxa |
| Disbiome | Disease-microbe associations | Disease-microbe links |
| BugSigDB | Microbial differential abundance signatures | Study-based signatures |
| gutMDisorder | Gut microbiota-disorder associations | Gut-disorder links |
| HMDB | Human metabolites | 6,534 metabolites |
| KEGG | Metabolic pathways | 1,710 pathways |
| ChEMBL | Drugs and protein targets | 6,220 drugs, 1,659 proteins |
| Reactome | Pathway and protein data | Pathway integration |
| PubMed | Scientific literature | 10,000 papers |
| PubChem | Chemical compounds | 32 compounds |
| Curated PRODUCES | Taxon-metabolite production | 231,556 relationships |
| Neurological diseases | Gut-brain axis associations | Curated associations |
Counts above are point-in-time snapshots and drift as new data loads — check
GET /api/v1/statsfor current live counts rather than treating this table as authoritative.
Taxon - Microbial organismsDisease - Human diseasesCompound - Chemical compounds and metabolites, from HMDB/PubChem/KEGG/etc.
(the canonical label — there is no separate Metabolite label)Pathway - Metabolic pathwaysGene - Genetic information (derived from Protein.gene_name, see below)Drug - Pharmaceutical compoundsProtein - Protein targetsPaper - Scientific literatureStudy - Research studiesBodySite - Body site/habitat locationsDrugClass - Drug classificationsHAS_PARENT - Taxonomic hierarchyEFFECTIVE_AGAINST - Antimicrobial resistancePRODUCES - Taxon → CompoundMENTIONED_IN - Entity → PaperASSOCIATED_WITH_DISEASE - Taxon → DiseasePARTICIPATES_IN - Compound/Gene → PathwayTARGETS - Drug → ProteinDGIDB_INTERACTS_WITH - Drug ↔ Gene interaction (kept distinct from INTERACTS_WITH, which is used for unrelated mined-literature predicates)ENCODED_BY - Protein → Gene (derived via the --derive maintenance flag)BELONGS_TO_CLASS - Drug → DrugClassPROCESSES - Metabolic processingLINKED_TO_DISEASE - Compound → DiseaseFOUND_IN - Taxon → BodySiteSAME_AS - Entity equivalenceIMPLICATED_IN - Pathway → Disease (derived mechanistic spine, via --derive)# Install dependencies
pip install -r requirements.txt
# Run locally
uvicorn api.main:app --reload --port 8200
# Run tests
pytest tests/
If you use MicroMap in your research, please cite it — see
CITATION.cff, or use the DOI directly:
10.5281/zenodo.22800749.
MicroMap is also listed in the KG-Registry, a community registry of knowledge graphs.
MIT — see LICENSE.