What organisms does the STRING database skill support?

The skill supports over 5,000 species, covering 59 million proteins, including humans, mice, and common model organisms.

How are protein interaction scores determined?

STRING assigns confidence scores (0-1000) based on various evidence types like experimental data, co-expression, and text-mining; this skill allows you to filter networks by these thresholds.

Can this skill generate visual network diagrams?

Yes, it can generate and save PNG images of interaction networks, with options to color lines by evidence type, confidence, or functional actions.

Can I perform Gene Ontology (GO) enrichment with this skill?

Yes, the skill includes specific functions to conduct functional enrichment analysis for GO terms, KEGG pathways, and Pfam protein domains.

STRING Database & Protein Analysis

Name: STRING Database & Protein Analysis
Author: x-cmd

byx-cmd

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Data Science & ML

Queries the STRING API to analyze protein-protein interaction networks and perform functional enrichment for systems biology.

About

This skill integrates the comprehensive STRING database into Claude, enabling researchers and bioinformaticians to explore protein-protein interaction networks across 59 million proteins and 5,000+ species. It provides specialized tools for identifier mapping, high-resolution network visualization, and statistical enrichment analysis across Gene Ontology (GO), KEGG pathways, and protein domains, making it an essential resource for characterizing biological pathways and interpreting omics data directly within your AI-driven workflow.

Key Features

Perform functional enrichment analysis for GO, KEGG, and Pfam domains
Calculate PPI enrichment statistics to identify functional modules
8 GitHub stars
Map gene and protein names to canonical STRING identifiers for 5000+ species
Retrieve interaction networks with evidence-based confidence scoring
Generate custom network visualizations as PNG images with evidence coloring

Use Cases

Discovering novel interaction partners and hub proteins for target genes
Analyzing differential expression or proteomics results for pathway enrichment
Comparing protein interaction patterns across different species

About

Key Features

Perform functional enrichment analysis for GO, KEGG, and Pfam domains
Calculate PPI enrichment statistics to identify functional modules
8 GitHub stars
Map gene and protein names to canonical STRING identifiers for 5000+ species
Retrieve interaction networks with evidence-based confidence scoring
Generate custom network visualizations as PNG images with evidence coloring

Use Cases

Discovering novel interaction partners and hub proteins for target genes
Analyzing differential expression or proteomics results for pathway enrichment
Comparing protein interaction patterns across different species