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To retrieve protein-protein interaction networks, you can query the STRING API using a list of proteins. The process maps your identifiers to STRING IDs and extracts interaction data with adjustable confidence score thresholds.

Yes, you can perform functional enrichment analysis using the STRING database. This feature assesses GO, KEGG, Pfam, InterPro, and SMART terms to evaluate network modularity and biological significance for your protein list.

Cross-species protein interaction comparisons are fully supported through taxon-specific queries. You can explore relationships across thousands of proteins by specifying different taxon identifiers during the STRING API data retrieval process.

Mapping protein identifiers to STRING IDs is handled automatically during the query workflow. The system accepts your input identifiers and translates them into the corresponding STRING IDs required for network retrieval and enrichment analyses.

Functional networks represent broader biological associations, while physical networks indicate direct physical contacts between proteins. You can configure the retrieval workflow to extract either network type based on your systems biology analysis requirements.

When analyzing large-scale protein interaction data, limitations depend on configured score thresholds and network types. Adjusting confidence scores is essential to filter low-confidence interactions and ensure meaningful PPI enrichment results across thousands of proteins.