STRING Database

Overview

STRING is a comprehensive database of known and predicted protein-protein interactions covering 59M proteins and 20B+ interactions across 5000+ organisms. Query interaction networks, perform functional enrichment, and discover partners via the REST API for systems biology and pathway analysis.

When to Use This Skill

Use this skill when:

• Retrieving protein-protein interaction networks for single or multiple proteins
• Performing functional enrichment (GO, KEGG, Pfam) on protein lists
• Discovering interaction partners and expanding protein networks
• Testing if proteins form significantly enriched functional modules
• Generating network visualizations with evidence-based coloring
• Analyzing homology and protein family relationships
• Conducting cross-species protein interaction comparisons
• Identifying hub proteins and network connectivity patterns

What This Skill Provides

1. Python helper functions (scripts/string_api.py) for all STRING REST API

operations.

1. Comprehensive reference documentation (references/string_reference.md) with

detailed endpoint and parameter specifications.

When a user requests STRING data, determine which operation is needed and use the appropriate function from scripts/string_api.py.

Core Workflow

1. Map identifiers first — string_map_ids() converts gene/protein names to

STRING IDs (format 9606.ENSP00000269305); always do this for speed and accuracy.

1. Retrieve the network or partners — string_network() for tabular

interaction data, string_interaction_partners() to expand from seeds, string_network_image() for a PNG figure.

1. Test and interpret — string_ppi_enrichment() checks whether the network

has more edges than chance; string_enrichment() runs GO/KEGG/Pfam enrichment (FDR < 0.05 = significant).

1. Compare / extend — string_homology() for family/paralog analysis;

repeat with other species for cross-species comparison.

1. Record version — string_version() for reproducibility.

The eight helper operations and five composed analysis workflows are documented in the references below.

Key Parameters

• `required_score` (confidence, 0-1000): 150 = low/exploratory, 400 =

medium/default, 700 = high/conservative, 900 = highest/very stringent. Lower = higher recall (more false positives); higher = higher precision.

• `network_type`: 'functional' (all evidence, default — pathway/systems

biology) or 'physical' (direct binding only — complexes, structural work).

• `species`: NCBI taxon ID (9606 human, 10090 mouse, 7227 fly, 4932 yeast,

6239 C. elegans, 7955 zebrafish, …). Required for networks > 10 proteins. Full list: https://string-db.org/cgi/input?input_page_active_form=organisms

API Best Practices

1. Always map identifiers first with string_map_ids().
2. Prefer STRING IDs (9606.ENSP00000269305) over gene names.
3. Specify species for networks > 10 proteins.
4. Respect rate limits — wait ~1 second between API calls.
5. Pin a version for reproducibility — set STRING_BASE_URL to a stable

subdomain (e.g. https://version-12-0.string-db.org/api) before running the helpers; see string_reference.md.

1. Handle errors gracefully — check for an "Error:" prefix in returned strings.
2. Match the confidence threshold to your analysis goals.

Routing Guidance

• **Need the exact code for one operation (ID mapping, network, image, partners,

functional enrichment, PPI enrichment, homology, version)?** Read references/operations.md.

• **Running an end-to-end analysis (protein-list, single-protein, pathway-centric,

cross-species, or network expansion)?** Read references/analysis-workflows.md.

• **Need endpoint specs, output formats (TSV/JSON/XML/PSI-MI), evidence-channel

details, advanced features, error handling, or tool integration (Cytoscape, R, Python)?** Read references/string_reference.md.

References

• references/operations.md — The eight scripts/string_api.py operations with

usage, parameters, output columns, and interpretation guidance.

• references/analysis-workflows.md — Five composed workflows: protein-list

analysis, single-protein investigation, pathway-centric analysis, cross-species comparison, and network expansion/discovery.

• references/string_reference.md — Complete API endpoint specifications, all

output formats, evidence channels and confidence-score details, advanced features (bulk upload, values/ranks enrichment), error handling, tool integration, and data license/citation.

Troubleshooting (Quick)

• No proteins found — verify species matches identifiers; map first; check

for typos.

• Empty network — lower required_score; confirm the proteins interact;

verify species.

• Timeout / slow — reduce input size; use STRING IDs; batch large queries.
• "Species required" error — add species for networks > 10 proteins.
• Unexpected results — check string_version(); verify network_type;

review the confidence threshold.

See references/string_reference.md for the full troubleshooting section.

Additional Resources

• Web app (proteome upload, complete network + function prediction):

https://string-db.org

• Bulk downloads (interactions, annotations, pathway mappings):

https://string-db.org/cgi/download

Data License and Citation

STRING data is freely available under Creative Commons BY 4.0 (free for academic and commercial use, attribution required). When publishing, cite the most recent STRING publication: https://string-db.org/cgi/about