# bedspace

> BEDspace applies the StarSpace model to genomic data, enabling simultaneous training of numerical embeddings for both region sets and their metadata labels

- Source: https://doutorai.pt/en/components/skills__bedspace
- Type: Skills
- Category: Scientific
- Downloads: 0
- Site: Doutor AI (https://doutorai.pt/en) - AI tools for small businesses

An open-source community component, curated and adapted by Doutor AI.

## What it does and how to use it

A **skill** that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.

1. Install the skill (command above).
2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
3. No commands to memorize: you talk in plain language and the skill does the rest.

## Install (Claude Code)

```bash
mkdir -p .claude/skills/bedspace && curl -fsSL https://doutorai.pt/data/lib/skills__bedspace.md -o .claude/skills/bedspace/SKILL.md
```

Paste this command into the terminal, in your project folder, and the component installs automatically.

## Content

```
# BEDspace: Joint Region and Metadata Embeddings

## Overview

BEDspace applies the StarSpace model to genomic data, enabling simultaneous training of numerical embeddings for both region sets and their metadata labels in a shared low-dimensional space. This allows for rich queries across regions and metadata.

## When to Use

Use BEDspace when working with:
- Region sets with associated metadata (cell types, tissues, conditions)
- Search tasks requiring metadata-aware similarity
- Cross-modal queries (e.g., "find regions similar to label X")
- Joint analysis of genomic content and experimenta

- 🔒 Full content on the Pro plan (€7.99/month) -
```

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Content by Doutor AI (https://doutorai.pt/en). When quoting, please cite the source: https://doutorai.pt/en/components/skills__bedspace