string-database

To retrieve a protein-protein interaction network, you query the STRING database by mapping your protein identifier to a STRING ID, then apply confidence thresholds and network-type filters to return interaction partners as TSV, JSON, or PNG outputs.

Yes, you can run functional enrichment analysis through the STRING API to identify overrepresented GO, KEGG, Pfam, InterPro, SMART, and UniProt keyword terms for your protein lists, returning structured results for downstream pathway analysis.

The best way to filter STRING interaction networks is by applying a required_score parameter, such as 700 for high-confidence interactions, alongside network-type filters to distinguish functional evidence from physical protein interactions.

STRING supports mapping common protein names to STRING IDs by using the get_string_ids REST API operation, which translates your input identifiers into the format required for retrieving interaction partners and building networks.

To test if your protein list is significantly interconnected, you run the STRING ppi_enrichment workflow, which evaluates whether the observed protein-protein interactions within your set occur more frequently than expected by chance.

Querying STRING protein interactions provides TSV, JSON, and PNG output formats, enabling you to directly utilize interaction partner lists, structured network data, and visual network images for downstream systems biology analysis.