A specialized bioinformatics skill for retrieving protein-protein interaction (PPI) networks and confidence scores from the STRING database.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ppi-string-query
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ppi-string-query using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is STRING Protein-Protein Interaction Query?
The ppi-string-query skill provides a programmatic interface to the STRING database, one of the world's most comprehensive resources for protein-protein interactions. By leveraging this tool within the Openclaw Skills ecosystem, developers can automate the retrieval of functional and physical protein associations based on UniProt identifiers.
This skill is designed to support researchers and developers building AI-driven biological discovery tools. It doesn't just return a list of partners; it provides granular confidence scores derived from experimental data, curated databases, and advanced text mining. This allows for the construction of highly reliable interaction networks tailored to specific research requirements.
STRING Protein-Protein Interaction Query Use Cases
- Finding interaction partners for specific proteins using UniProt IDs.
- Constructing protein interaction networks for downstream pathway analysis.
- Retrieving weighted confidence scores to validate the reliability of biological interactions.
- Identifying potential protein complexes or functional modules within a specific organism.
- Automating data collection for proteomics research within Openclaw Skills workflows.
How STRING Protein-Protein Interaction Query Works
- The user provides a UniProt accession code and specifies the target organism using an NCBI taxonomy ID.
- The skill communicates with the STRING database API to fetch protein association data.
- Results are filtered based on the requested confidence threshold (ranging from low to highest confidence).
- The tool returns a structured JSON object containing the interaction partners, gene names, and a detailed breakdown of evidence scores.
STRING Protein-Protein Interaction Query Setup
To utilize this skill, ensure you have the open-biomed toolkit installed in your environment. You can integrate it into your Openclaw Skills project using the following steps:
pip install open-biomed
Initialize the tool in your Python logic:
from open_biomed.tools.tool_registry import TOOLS
tool = TOOLS["ppi_string_request"]
STRING Protein-Protein Interaction Query Data Schema & Taxonomy
The skill returns a list of interaction objects. Below is the schema for the returned metadata:
| Property | Description | Data Type |
|---|---|---|
query_protein |
The identifier used for the query | String |
partner_gene |
The gene symbol of the interacting partner | String |
combined_score |
The overall confidence score (0 to 1) | Float |
scores |
Detailed breakdown (experimental, text_mining, database) | Object |
ncbi_taxon_id |
The NCBI taxonomy ID for the species | Integer |
STRING Protein-Protein Interaction Query Advanced Features
- Support for multiple organism taxonomies, including Human (9606), Mouse (10090), and Rat (10116).
- Customizable confidence thresholds allowing for exploratory analysis (150) or high-stringency validation (900).
- Comprehensive evidence channel breakdown, including gene fusion, co-expression, and phylogenetic profiles.
- Rate-limit aware processing to ensure stable connectivity with the STRING API during high-volume Openclaw Skills executions.
SKILL.md
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