Which biological tasks can Biomni automate?

It excels at CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction for drug candidates, and clinical genomics for rare disease diagnosis.

What is the Biomni Claude Code Skill?

Biomni is an autonomous agent framework from Stanford's SNAP lab that helps users conduct complex biomedical research tasks like GWAS analysis and molecular biology simulations using natural language.

Does Biomni require a specific dataset?

Yes, Biomni integrates approximately 11GB of biomedical knowledge sources including Ensembl, UniProt, and PubMed, which are typically downloaded on first use.

Is it safe to run code generated by Biomni?

Biomni executes generated code with system privileges. It is recommended to run it in isolated environments like Docker or virtual machines for production use.

Which LLM models work best with Biomni?

Claude 3.5 Sonnet and Opus are highly recommended for their balance of biological reasoning capabilities and execution speed.

Biomni Biomedical AI Agent

Name: Biomni Biomedical AI Agent
Author: Activer007

byActiver007

0•

数据科学与机器学习

Executes complex biomedical research tasks including genomics analysis, drug discovery, and clinical data interpretation through autonomous AI agents.

Biomni is an open-source biomedical AI framework developed by Stanford's SNAP lab that enables Claude to autonomously perform multi-step research across genomics, molecular biology, and drug discovery. By combining LLM reasoning with dynamic code execution and a massive 11GB integrated biomedical database, it streamlines workflows for CRISPR design, single-cell RNA-seq analysis, ADMET prediction, and GWAS interpretation. It is designed for researchers and bioinformaticians who need a specialized tool for high-level biological reasoning and automated data analysis pipelines.

主要功能

01Integrated access to 11GB of gene, protein, and clinical databases

02Dynamic Python code generation and execution for data pipelines

03Cross-domain problem solving for genomics and drug discovery

04Built-in evaluation framework for benchmarking research performance

05Autonomous multi-step biological reasoning and task planning

060 GitHub stars

使用场景

01Designing genome-wide CRISPR knockout screens and gene prioritization

02End-to-end single-cell RNA-seq clustering and cell type annotation

03Predicting ADMET properties and performing target identification for drug discovery

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