119 String 196e9adf

STRING Database API Reference

Overview

STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) is a comprehensive database of known and predicted protein-protein interactions integrating data from over 40 sources.

Database Statistics (v12.0+):

• Coverage: 5000+ genomes
• Proteins: ~59.3 million
• Interactions: 20+ billion
• Data types: Physical interactions, functional associations, co-expression, co-occurrence, text-mining, databases

Core Data Resource: Designated by Global Biodata Coalition and ELIXIR

API Base URLs

• Current version: https://string-db.org/api
• Version-specific: https://version-12-0.string-db.org/api (for reproducibility)
• API documentation: https://string-db.org/help/api/

Best Practices

1. Identifier Mapping: Always map identifiers first using get_string_ids for faster subsequent queries
2. Use STRING IDs: Prefer STRING identifiers (e.g., 9606.ENSP00000269305) over gene names
3. Specify Species: For networks with >10 proteins, always specify species NCBI taxon ID
4. Rate Limiting: Wait 1 second between API calls to avoid server overload
5. Versioned URLs: Use version-specific URLs for reproducible research
6. POST over GET: Use POST requests for large protein lists
7. Caller Identity: Include caller_identity parameter for tracking (e.g., your application name)

API Methods

1. Identifier Mapping (get_string_ids)

Purpose: Maps common protein names, gene symbols, UniProt IDs, and other identifiers to STRING identifiers.

Endpoint: /api/tsv/get_string_ids

Parameters:

• identifiers (required): Protein names/IDs separated by newlines (%0d)
• species (required): NCBI taxon ID
• limit: Number of matches per identifier (default: 1)
• echo_query: Include query term in output (1 or 0)
• caller_identity: Application identifier

Output Format: TSV with columns:

• queryItem: Original query
• queryIndex: Query position
• stringId: STRING identifier
• ncbiTaxonId: Species taxon ID
• taxonName: Species name
• preferredName: Preferred gene name
• annotation: Protein description

Example:

identifiers=TP53%0dBRCA1&species=9606&limit=1

Use cases:

• Converting gene symbols to STRING IDs
• Validating protein identifiers
• Finding canonical protein names

2. Network Data (network)

Purpose: Retrieves protein-protein interaction network data in tabular format.

Endpoint: /api/tsv/network

Parameters:

• identifiers (required): Protein IDs separated by %0d
• species: NCBI taxon ID
• required_score: Confidence threshold 0-1000 (default: 400)
  • 150: low confidence
  • 400: medium confidence
  • 700: high confidence
  • 900: highest confidence
• network_type: functional (default) or physical
• add_nodes: Add N interacting proteins (0-10)
• caller_identity: Application identifier

Output Format: TSV with columns:

• stringId_A, stringId_B: Interacting proteins
• preferredName_A, preferredName_B: Gene names
• ncbiTaxonId: Species
• score: Combined interaction score (0-1000)
• nscore: Neighborhood score
• fscore: Fusion score
• pscore: Phylogenetic profile score
• ascore: Coexpression score
• escore: Experimental score
• dscore: Database score
• tscore: Text-mining score

Network Types:

• Functional: All interaction evidence types (recommended for most analyses)
• Physical: Only direct physical binding evidence

Example:

identifiers=9606.ENSP00000269305%0d9606.ENSP00000275493&required_score=700

3. Network Image (image/network)

Purpose: Generates visual network representation as PNG image.

Endpoint: /api/image/network

Parameters:

• identifiers (required): Protein IDs separated by %0d
• species: NCBI taxon ID
• required_score: Confidence threshold 0-1000
• network_flavor: Visualization style
  • evidence: Show evidence types as colored lines
  • confidence: Show confidence as line thickness
  • actions: Show activating/inhibiting interactions
• add_nodes: Add N interacting proteins (0-10)
• caller_identity: Application identifier

Output: PNG image (binary data)

Image Specifications:

• Format: PNG
• Size: Automatically scaled based on network size
• High-resolution option available (add ?highres=1)

Example:

identifiers=TP53%0dMDM2&species=9606&network_flavor=evidence

4. Interaction Partners (interaction_partners)

Purpose: Retrieves all STRING interaction partners for given protein(s).

Endpoint: /api/tsv/interaction_partners

Parameters:

• identifiers (required): Protein IDs
• species: NCBI taxon ID
• required_score: Confidence threshold 0-1000
• limit: Maximum number of partners (default: 10)
• caller_identity: Application identifier

Output Format: TSV with same columns as network method

Use cases:

• Finding hub proteins
• Expanding networks
• Discovery of novel interactions

Example:

identifiers=TP53&species=9606&limit=20&required_score=700

5. Functional Enrichment (enrichment)

Purpose: Performs functional enrichment analysis for a set of proteins across multiple annotation databases.

Endpoint: /api/tsv/enrichment

Parameters:

• identifiers (required): List of protein IDs
• species (required): NCBI taxon ID
• caller_identity: Application identifier

Enrichment Categories:

• Gene Ontology: Biological Process, Molecular Function, Cellular Component
• KEGG Pathways: Metabolic and signaling pathways
• Pfam: Protein domains
• InterPro: Protein families and domains
• SMART: Domain architecture
• UniProt Keywords: Curated functional keywords

Output Format: TSV with columns:

• category: Annotation category
• term: Term ID
• description: Term description
• number_of_genes: Genes in input with this term
• number_of_genes_in_background: Total genes with this term
• ncbiTaxonId: Species
• inputGenes: Comma-separated gene list
• preferredNames: Comma-separated gene names
• p_value: Enrichment p-value (uncorrected)
• fdr: False discovery rate (corrected p-value)

Statistical Method: Fisher's exact test with Benjamini-Hochberg FDR correction

Example:

identifiers=TP53%0dMDM2%0dATM%0dCHEK2&species=9606

6. PPI Enrichment (ppi_enrichment)

Purpose: Tests if a network has significantly more interactions than expected by chance.

Endpoint: /api/json/ppi_enrichment

Parameters:

• identifiers (required): List of protein IDs
• species: NCBI taxon ID
• required_score: Confidence threshold
• caller_identity: Application identifier

Output Format: JSON with fields:

• number_of_nodes: Proteins in network
• number_of_edges: Interactions observed
• expected_number_of_edges: Expected interactions (random)
• p_value: Statistical significance

Interpretation:

• p-value < 0.05: Network is significantly enriched
• Low p-value indicates proteins form functional module

Example:

identifiers=TP53%0dMDM2%0dATM%0dCHEK2&species=9606

7. Homology Scores (homology)

Purpose: Retrieves protein similarity/homology scores.

Endpoint: /api/tsv/homology

Parameters:

• identifiers (required): Protein IDs
• species: NCBI taxon ID
• caller_identity: Application identifier

Output Format: TSV with homology scores between proteins

Use cases:

• Identifying protein families
• Paralog analysis
• Cross-species comparisons

8. Version Information (version)

Purpose: Returns current STRING database version.

Endpoint: /api/tsv/version

Output: Version string (e.g., "12.0")

Common Species NCBI Taxon IDs

Full list: https://string-db.org/cgi/input?input_page_active_form=organisms

STRING Identifier Format

STRING uses Ensembl protein IDs with taxon prefix:

• Format: {taxonId}.{ensemblProteinId}
• Example: 9606.ENSP00000269305 (human TP53)

ID Components:

• Taxon ID: NCBI taxonomy identifier
• Protein ID: Usually Ensembl protein ID (ENSP...)

Interaction Confidence Scores

STRING provides combined confidence scores (0-1000) based on multiple evidence channels:

Evidence Channels

1. Neighborhood (nscore): Gene fusion and conserved genomic neighborhood
2. Fusion (fscore): Gene fusion events across species
3. Phylogenetic Profile (pscore): Co-occurrence across species
4. Coexpression (ascore): RNA expression correlation
5. Experimental (escore): Biochemical/genetic experiments
6. Database (dscore): Curated pathway/complex databases
7. Text-mining (tscore): Literature co-occurrence

Recommended Thresholds

• 150: Low confidence (exploratory analysis)
• 400: Medium confidence (standard analysis)
• 700: High confidence (conservative analysis)
• 900: Highest confidence (very stringent)

Output Formats

Available Formats

1. TSV: Tab-separated values (default, best for data processing)
2. JSON: JavaScript Object Notation (structured data)
3. XML: Extensible Markup Language
4. PSI-MI: Proteomics Standards Initiative format
5. PSI-MITAB: Tab-delimited PSI-MI format
6. PNG: Image format (for network visualizations)
7. SVG: Scalable vector graphics (for network visualizations)

Format Selection

Replace /tsv/ in URL with desired format:

• /json/network - JSON format
• /xml/network - XML format
• /image/network - PNG image

Error Handling

HTTP Status Codes

• 200 OK: Successful request
• 400 Bad Request: Invalid parameters or syntax
• 404 Not Found: Protein/species not found
• 500 Internal Server Error: Server error

Common Errors

1. "No proteins found": Invalid identifiers or species mismatch
2. "Species required": Missing species parameter for large networks
3. Empty results: No interactions above score threshold
4. Timeout: Network too large, reduce protein count

Advanced Features

Bulk Network Upload

For complete proteome analysis:

1. Navigate to https://string-db.org/
2. Select "Upload proteome" option
3. Upload FASTA file
4. STRING generates complete interaction network and predicts functions

Values/Ranks Enrichment API

For differential expression/proteomics data:

1. Get API Key:

/api/json/get_api_key

2. Submit Data: Tab-separated protein ID and value pairs

3. Check Status:

/api/json/valuesranks_enrichment_status?job_id={id}

4. Retrieve Results: Access enrichment tables and figures

Requirements:

• Complete protein set (no filtering)
• Numeric values for each protein
• Proper species identifier

Network Customization

Network Size Control:

• add_nodes=N: Adds N most connected proteins
• limit: Controls partner retrieval

Confidence Filtering:

• Adjust required_score based on analysis goals
• Higher scores = fewer false positives, more false negatives

Network Type Selection:

• functional: All evidence (recommended for pathway analysis)
• physical: Direct binding only (recommended for structural studies)

Integration with Other Tools

Python Libraries

requests (recommended):

import requests
url = "https://string-db.org/api/tsv/network"
params = {"identifiers": "TP53", "species": 9606}
response = requests.get(url, params=params)

urllib (standard library):

import urllib.request
url = "https://string-db.org/api/tsv/network?identifiers=TP53&species=9606"
response = urllib.request.urlopen(url)

R Integration

STRINGdb Bioconductor package:

library(STRINGdb)
string_db <- STRINGdb$new(version="12", species=9606)

Cytoscape

STRING networks can be imported into Cytoscape for visualization and analysis:

1. Use stringApp plugin
2. Import TSV network data
3. Apply layouts and styling

Data License

STRING data is freely available under Creative Commons BY 4.0 license:

• ✓ Free to use for academic and commercial purposes
• ✓ Attribution required
• ✓ Modifications allowed
• ✓ Redistribution allowed

Citation: Szklarczyk et al. (latest publication)

Rate Limits and Usage

• Rate limiting: No strict limit, but avoid rapid-fire requests
• Recommendation: Wait 1 second between calls
• Large datasets: Use bulk download from https://string-db.org/cgi/download
• Proteome-scale: Use web upload feature instead of API

Related Resources

• STRING website: https://string-db.org
• Download page: https://string-db.org/cgi/download
• Help center: https://string-db.org/help/
• API documentation: https://string-db.org/help/api/
• Publications: https://string-db.org/cgi/about

Troubleshooting

No results returned:

• Verify species parameter matches identifiers
• Check identifier format
• Lower confidence threshold
• Use identifier mapping first

Timeout errors:

• Reduce number of input proteins
• Split large queries into batches
• Use bulk download for proteome-scale analyses

Version inconsistencies:

• Use version-specific URLs
• Check STRING version with /version endpoint
• Update identifiers if using old IDs