alterlab-string-db

Map protein identifiers to STRING IDs and retrieve interaction networks and enrichment results.

58|9|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-string-db
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: alterlab-string-db
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/databases/alterlab-string-db
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-string-db

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

STRING provides access to massive protein-protein interaction data and enrichment analyses, enabling researchers to gather interaction networks and functional context for proteins of interest.

Core Features & Use Cases

  • Map gene/protein names to STRING IDs to standardize identifiers and enable downstream queries.
  • Retrieve protein-protein interaction networks and expand results with added nodes.
  • Perform functional enrichment (GO, KEGG, Pfam, InterPro) on protein lists and generate interpretable outputs.
  • Compare interactions across species and generate network visualizations for reporting.

Quick Start

Map a list of proteins to STRING IDs, fetch their interaction network, and run a basic enrichment analysis.

Frequently Asked Questions about alterlab-string-db

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I map gene or protein names to STRING IDs for protein interaction network analysis?

Protein identifier mapping converts standard gene or protein names into STRING IDs, standardizing inputs to enable downstream protein interaction network retrieval and functional enrichment queries.

How do I retrieve a protein-protein interaction network and run functional enrichment analysis?

Functional enrichment analysis retrieves protein-protein interaction networks from STRING and calculates GO, KEGG, Pfam, and InterPro annotations to generate interpretable functional context outputs for protein lists.

Can I compare protein interactions across species and generate network visualizations?

Cross-species comparisons query STRING interaction data across different organisms and generate network visualizations, allowing researchers to identify conserved interactions and report comparative network structures.

What is the best way to find hub proteins in a protein-protein interaction network from STRING?

Hub detection within a protein-protein interaction network identifies highly connected nodes using STRING data, applying Python helper functions to map identifiers and construct networks for centrality analysis.

Do I need to format my protein lists in a specific way before mapping them to STRING IDs?

Protein lists require standard gene or protein names as input before mapping them to STRING IDs, ensuring the identifier mapping process accurately retrieves interaction networks and enrichment results.

What types of enrichment outputs can I expect from STRING protein interaction queries?

STRING protein interaction queries yield functional enrichment outputs covering GO terms, KEGG pathways, Pfam domains, and InterPro entries, providing interpretable biological context for the analyzed protein network.