string-database-ppi
Query STRING REST API for PPIs (59M proteins, 20B interactions, 5000+ species). Retrieve networks, run GO/KEGG enrichment, find partners, test PPI significance, visualize networks, analyze homology. For chemical interactions use chembl-database-bioactivity; pathways use kegg-database.
npx skills add BioTender-max/awesome-bio-agent-skills --skill string-database-ppi --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# STRING Database — Protein-Protein Interactions ## Overview Query the STRING protein-protein interaction database (59M proteins, 20B+ interactions, 5000+ species) via REST API. Covers network retrieval, functional enrichment (GO, KEGG, Pfam), interaction partner discovery, PPI enrichment testing, network visualization, and homology analysis. ## When to Use - Retrieving protein-protein interaction networks for one or multiple proteins - Performing functional enrichment analysis (GO, KEGG, Pfam, InterPro) on protein lists - Discovering interaction partners and expanding protein networks from seed proteins - Testing whether a set of proteins forms a significantly enriched functional module - Generating network visualizations with evidence-based coloring - Analyzing homology and protein family relationships across species - Identifying hub proteins and network connectivity patterns - For chemical compound interactions use chembl-database-bioactivity instead; for pathway-centric queries use kegg-database ## Prerequisites ```bash uv pip install requests pandas ``` **Rate limiting**: No strict rate limit, but wait ~1 second between API calls. For proteome-scale analyses, use bulk downloa
- Overview
- When to Use
- Prerequisites
- Quick Start
- Key Concepts
- Common Species NCBI Taxon IDs
- STRING Identifier Format
- Interaction Confidence Scores
- Network Types
- Output Formats
- Core API
- 1. Identifier Mapping
- 2. Network Retrieval
- 3. Network Visualization
uv pip install requests pandas
What does the string-database-ppi skill do?
Query STRING REST API for PPIs (59M proteins, 20B interactions, 5000+ species). Retrieve networks, run GO/KEGG enrichment, find partners, test PPI significance, visualize networks, analyze homology. For chemical interactions use chembl-database-bioactivity; pathways use kegg-database.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill string-database-ppi --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.