What is the Biomni Claude Code skill?

Biomni is a specialized capability for Claude that transforms it into an autonomous biomedical researcher capable of handling complex tasks in genomics, molecular biology, and drug discovery.

Which LLM models are recommended for Biomni?

While it supports various providers, Anthropic Claude 3.5 Sonnet is the recommended model for its superior reasoning capabilities in biological contexts.

Is it safe to run Biomni locally?

Biomni executes LLM-generated code with full system privileges. For security, it is recommended to run the agent in isolated environments like Docker or VMs.

How does Biomni access biological data?

Biomni integrates a curated 11GB data lake including Ensembl, UniProt, ClinVar, and PubMed, which is automatically downloaded during the first use.

Can Biomni perform data analysis on my local files?

Yes, Biomni can generate and execute Python code to process local datasets such as .h5ad files for RNA-seq or summary statistics for GWAS.

Biomni Biomedical AI Agent

Name: Biomni Biomedical AI Agent
Author: Activer007

byActiver007

0•

数据科学与机器学习

Empowers biomedical researchers with autonomous agents for complex genomics, drug discovery, and clinical data analysis.

Biomni is a specialized framework developed by Stanford's SNAP lab that enables Claude to act as an autonomous biomedical research agent. It bridges the gap between biological reasoning and technical execution by combining multi-step planning with dynamic code generation and an integrated 11GB database of biological knowledge. Whether you are designing CRISPR screens, analyzing single-cell RNA-seq data, or predicting drug ADMET properties, Biomni provides a unified interface to execute sophisticated bioinformatics workflows and interpret complex biological results.

主要功能

01Integrated 11GB data lake covering genomics, proteomics, and literature

02Automated PDF reporting for research reproducibility and documentation

03Autonomous multi-step biological reasoning and task planning

04Dynamic code generation and execution for data processing pipelines

05Cross-domain problem solving from molecular biology to clinical analysis

060 GitHub stars

使用场景

01Designing genome-wide CRISPR knockout screens and prioritizing candidate genes

02Predicting drug ADMET properties and performing GWAS variant interpretation

03End-to-end single-cell RNA-seq analysis including clustering and cell type annotation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add activer007/ordinary-claude-skills biomni

For use in Claude.ai and ChatGPT

Download Skill