Is it possible to visualize the networks?

Yes, the skill can generate and save PNG images of interaction networks with customizable coloring based on evidence types, confidence levels, or biological actions.

What types of interaction evidence are provided?

The skill retrieves evidence scores from multiple sources, including genomic neighborhood, gene fusion, co-occurrence, co-expression, experimental data, curated databases, and text-mining.

Can I use this skill to perform pathway analysis?

Yes, the skill includes functional enrichment for KEGG pathways, Gene Ontology (GO), and Pfam domains to characterize protein lists.

What organisms does the STRING database skill support?

It supports over 5000 species, including humans (NCBI taxon 9606), mice (10090), and fruit flies (7227).

How does the skill handle different protein identifiers?

It includes a dedicated mapping operation that converts common gene names, protein names, and external IDs into canonical STRING identifiers for accurate querying.

STRING Protein Interaction Database

Name: STRING Protein Interaction Database
Author: ricable

byricable

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数据科学与机器学习

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

关于

The STRING Database skill integrates the comprehensive STRING API into the Claude Code environment, allowing researchers and bioinformaticians to map protein identifiers, retrieve complex interaction networks, and perform statistical enrichment analysis. Covering over 5000 species and billions of interactions, it facilitates the discovery of protein partners, pathway analysis, and network visualization directly within a development or analysis workflow, streamlining the interpretation of proteomics and genomics data.

主要功能

Conducts PPI enrichment tests to determine statistical significance of network modules
Maps gene and protein identifiers to canonical STRING IDs across 5000+ species
Performs functional enrichment analysis using GO, KEGG, Pfam, and InterPro databases
Retrieves high-confidence protein-protein interaction (PPI) networks with evidence scores
Generates evidence-based network visualizations in PNG format
1 GitHub stars

使用场景

Identifying hub proteins and novel interaction partners for specific biological targets
Analyzing differentially expressed protein lists from proteomics or transcriptomics experiments
Validating the functional connectivity of protein clusters using statistical enrichment analysis

关于

主要功能

Conducts PPI enrichment tests to determine statistical significance of network modules
Maps gene and protein identifiers to canonical STRING IDs across 5000+ species
Performs functional enrichment analysis using GO, KEGG, Pfam, and InterPro databases
Retrieves high-confidence protein-protein interaction (PPI) networks with evidence scores
Generates evidence-based network visualizations in PNG format
1 GitHub stars

使用场景

Identifying hub proteins and novel interaction partners for specific biological targets
Analyzing differentially expressed protein lists from proteomics or transcriptomics experiments
Validating the functional connectivity of protein clusters using statistical enrichment analysis