# geniml

> This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, B

- Source: https://doutorai.pt/en/components/skills__geniml
- Type: Skills
- Category: Scientific
- Downloads: 8
- 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/geniml && curl -fsSL https://doutorai.pt/data/lib/skills__geniml.md -o .claude/skills/geniml/SKILL.md
```

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

## Content

```
---
name: geniml
description: This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
---

# Geniml: Genomic Interval Machine Learning

## Overview

Geniml is a Python package for building machine learning models on genomic interval data fr

- 🔒 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__geniml