Skill-Details

string-database

Useful for biological network analysis.

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Quellegoogle-deepmind/science-skillsExterne Quelle
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SKILL.md

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---
name: string-database
description: >
  Query the STRING database for protein-protein interactions (PPIs), functional
  enrichment, and homology. Use when the user asks about interactions between
  specific proteins, interaction evidence, confidence scores, protein
  interaction partners, or pathway enrichments.
---

# STRING Database Skill

This skill allows you to query the STRING database programmatically using a
bundled Python CLI wrapper.

## Prerequisites

1.  **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure
    `uv` is installed and on PATH.
2.  **User Notification**: If .licenses/string_database_LICENSE.txt does not
    already exist in the workspace root directory then (1) prominently notify
    the user to check the terms at https://string-db.org/cgi/access, then (2)
    create the file recording the notification text and timestamp.

## Core Rules

1.  **MANDATORY: Ask for Species First:** The STRING API requires NCBI Taxon
    IDs. **You MUST NOT guess or assume a species.** If the user does not
    explicitly state a species or Taxon ID, you MUST stop and ask: "Which
    species are you interested in? I need the NCBI Taxon ID to proceed." Even
    for well-known proteins like TP53, BRCA1, or MDM2 that are commonly
    associated with human studies, you MUST still ask — do not default to Human.
2.  **Never print output to stdout:** The `--output <file.tsv>` is required.
    Never read large outputs into context. Instead use jq, python or file
    operations (`grep`, `head`) to process large output.
3.  **Map Identifiers first:** If you only have common gene names (e.g.,
    'TP53'), map them to STRING IDs first as this guarantees much faster server
    responses. Use the `map` command for this.
4.  **Notification**: If this skill is used, ensure this is mentioned in the
    output.

## Tool Execution

The CLI is at `scripts/string_cli.py` and should be run using `uv run`:

```bash
uv run scripts/string_cli.py <command> [options] --output /tmp/out.tsv
```

## Feature Domains (Progressive Disclosure)

Read the following reference files based on the user's request:

*   **[Mapping Identifiers](references/mapping.md)** - Map common protein names
    to STRING IDs.
*   **[Interactions & Network](references/interactions.md)** - Find interacting
    proteins, network topologies, mediators, homology, and visual network
    images.
*   **[Enrichment & Functional Annotations](references/enrichment.md)** -
    Analyze pathway enrichment (GO, KEGG, Pfam), PPI significance, or find all
    proteins associated with a specific term (e.g. Melanoma).
*   **[Values/Ranks Enrichment](references/valuesranks.md)** - Submit full
    experimental datasets (e.g., logFC, p-values) for rank-based enrichment
    analysis using the async background API.

To begin, read the reference file most appropriate to the current task to
discover the correct CLI command.
Vollständige Quelle auf GitHub lesen (öffnet externe Seite)
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