Can I visualize protein networks directly with this skill?

Yes, the skill can generate network visualizations as PNG images with different flavors, including evidence-based coloring, confidence-based line thickness, and action-based relationships.

What organisms are supported by the STRING database skill?

The skill supports over 5,000 species, including common model organisms like humans (9606), mice (10090), fruit flies (7227), and yeast (4932).

How does the skill handle different protein naming conventions?

It includes a mapping operation that converts gene names, protein names, and various external IDs into canonical STRING identifiers to ensure query accuracy.

What types of functional enrichment does it perform?

It performs enrichment analysis across multiple categories including Gene Ontology (GO), KEGG pathways, Pfam domains, InterPro families, and UniProt keywords.

STRING Protein Interaction Database

Name: STRING Protein Interaction Database
Author: K-Dense-AI

byK-Dense-AI

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2,188

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Ciencia de Datos y ML

Analyzes protein-protein interaction networks and performs functional enrichment using the STRING database's 20 billion interactions.

This skill connects Claude to the STRING database, providing a robust interface for systems biology and bioinformatics research. It allows users to query protein-protein interaction (PPI) networks for over 5,000 species, perform functional enrichment analysis across GO and KEGG pathways, and generate visual network representations. By automating ID mapping and statistical testing for network connectivity, it streamlines the interpretation of proteomics and genomics data directly within the development environment.

Características Principales

01Functional enrichment analysis for GO terms, KEGG, and Pfam domains

02Identifier mapping for genes and proteins across 5,000+ species

03Statistical PPI enrichment testing to validate functional modules

04Retrieval of interaction networks with customizable confidence thresholds

052,188 GitHub stars

06Automated network visualization with evidence-based coloring

Casos de Uso

01Interpreting proteomics data by identifying significant functional pathways

02Building and visualizing protein interaction networks for research publications

03Discovering novel protein partners and analyzing network connectivity patterns

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add k-dense-ai/claude-scientific-skills string-database

For use in Claude.ai and ChatGPT

Download Skill