# region2vec

> Region2Vec generates unsupervised embeddings of genomic regions and region sets from BED files. It maps genomic regions to a vocabulary, creates sentences 

- Source: https://doutorai.pt/en/components/skills__region2vec
- 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/region2vec && curl -fsSL https://doutorai.pt/data/lib/skills__region2vec.md -o .claude/skills/region2vec/SKILL.md
```

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

## Content

```
# Region2Vec: Genomic Region Embeddings

## Overview

Region2Vec generates unsupervised embeddings of genomic regions and region sets from BED files. It maps genomic regions to a vocabulary, creates sentences through concatenation, and applies word2vec training to learn meaningful representations.

## When to Use

Use Region2Vec when working with:
- BED file collections requiring dimensionality reduction
- Genomic region similarity analysis
- Downstream ML tasks requiring region feature vectors
- Comparative analysis across multiple genomic datasets

## Workflow

### Step 1: Prepare Data

Gath

- 🔒 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__region2vec