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DataPython

Arboreto

by FreedomIntelligence

Arboreto is a Data skill for Claude Code, published by FreedomIntelligence in OpenClaw-Medical-Skills.

2.9K stars410 forkson FreedomIntelligence/OpenClaw-Medical-SkillsAdded 2026/08/17Repository updated 2026/07/21

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Install in seconds

Install Arboreto

Copy Arboreto into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/arboreto ~/.claude/skills/arboreto

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/arboreto/SKILL.md in FreedomIntelligence/OpenClaw-Medical-Skills
Installs to: ~/.claude/skills/arboreto
Collection: One of 25 skills cataloged from this repository
Category: Data — 668 skills

What Arboreto does

Arboreto infers gene regulatory networks from gene expression data using scalable algorithms such as GRNBoost2 and GENIE3. Use it to identify transcription factor–target relationships in bulk or single-cell RNA-seq, with optional distributed computing for large datasets.

Arboreto is cataloged under Data on DirSkills. Arboreto comes from a repository tagged awesome, claude-code, clawhub, medical and nanoclaw.

Documentation

README

Excerpt

Arboreto

Overview

Arboreto is a computational library for inferring gene regulatory networks (GRNs) from gene expression data using parallelized algorithms that scale from single machines to multi-node clusters.

Core capability: Identify which transcription factors (TFs) regulate which target genes based on expression patterns across observations (cells, samples, conditions).

Quick Start

Install arboreto:

uv pip install arboreto

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Arboreto

What else does FreedomIntelligence publish alongside Arboreto?
Arboreto is one of 25 skills that DirSkills catalogs from FreedomIntelligence/OpenClaw-Medical-Skills, the repository it ships in. Its siblings there include AAV Vector Design Agent, ADHD Daily Planner and ADMET Prediction. Each one is a separate skill with its own page in this directory, installs the same way Arboreto does, and is maintained by FreedomIntelligence in that same repository. The rest of the collection is listed on the FreedomIntelligence/OpenClaw-Medical-Skills page.
How does Arboreto compare to other Data skills?
Arboreto ranks #262 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Arboreto against them. Open each page to compare what they document and how they install.

More from FreedomIntelligence/OpenClaw-Medical-Skills

Arboreto is one of 25 skills cataloged on DirSkills from FreedomIntelligence/OpenClaw-Medical-Skills.

See all 25 skills →

AAV Vector Design Agent

AAV Vector Design Agent designs adeno-associated virus vectors for gene therapy by selecting serotypes, engineering capsids, optimizing promoters and transgenes, and predicting immunogenicity. Use it when designing tissue-specific AAV vectors, engineering capsid variants, or optimizing expression cassettes.

ADHD Daily Planner

ADHD Daily Planner provides ADHD-specific daily planning, time estimation, and executive function support. Use it to create realistic schedules and build flexible systems that work with ADHD brains.

ADMET Prediction

ADMET Prediction predicts ADMET properties (absorption, distribution, metabolism, excretion, toxicity) using ADMETlab 3.0 API or DeepChem models, including bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty quantification. It filters compounds for PAINS and other structural alerts to assess drug-likeness and prioritize leads by predicted safety.

AI Health Analyzer

AI Health Analyzer integrates multi-dimensional health data to identify abnormal patterns, predict health risks, and provide personalized recommendations. Use it for intelligent health Q&A and AI-generated health reports.

Adaptyv

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Aeon Time Series ML

Aeon Time Series ML provides scikit-learn compatible algorithms for time series classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use it when working with temporal data or sequential patterns that require specialized approaches beyond standard ML.

More Data skills

Arboreto is one of 668 Data skills cataloged on DirSkills, ranked #262 by stars among them.

Browse all Data skills →

Benchmark Methodology

Benchmark Methodology scores competitors across nine weighted dimensions using explicit 1–5 rubrics and a tension plot. Use it after competitive-platform-analysis to produce comparable, evidence-anchored profile cards for a competitive report.

Jupyter Notebook

Jupyter Notebook provides a stateful Python REPL via a live Jupyter kernel (hamelnb) so variables persist across executions. Use it for iterative data exploration, API inspection, and complex code development.

Solana

Solana queries wallets, token holdings, transactions, NFTs, whale transfers, and network stats on the Solana blockchain with USD pricing via CoinGecko. Use it when you need to inspect an address, verify a transaction, check token metadata or prices, or monitor network health.