Is Biomni safe for local code execution?

Biomni executes LLM-generated code with system privileges. It is highly recommended to run the tool in isolated environments like Docker or virtual machines for security.

Which LLM models work best with Biomni?

Claude 3.5 Sonnet is highly recommended for its exceptional balance of speed, cost, and high-quality biological reasoning capabilities.

Can Biomni help with clinical genomics?

Yes, Biomni supports clinical tasks including rare disease diagnosis, variant pathogenicity interpretation, and phenotype-genotype mapping.

Biomni is an open-source autonomous agent framework developed by Stanford SNAP lab for executing complex biomedical research tasks using LLMs and integrated databases.

Do I need to provide my own biological data?

While you can provide your own datasets, Biomni automatically downloads and integrates approximately 11GB of biomedical knowledge sources upon its first use to assist in reasoning.

Biomni Biomedical AI Agent

Name: Biomni Biomedical AI Agent
Author: Microck

byMicrock

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Data Science & ML

Automates complex biomedical research tasks including genomics, drug discovery, and clinical analysis through autonomous agent reasoning.

About

Biomni is a specialized autonomous agent framework designed for the biomedical domain, originating from Stanford's SNAP lab. It enables Claude to execute multi-step research workflows such as CRISPR screening design, single-cell RNA-seq analysis, and ADMET prediction by combining LLM reasoning with code execution and access to an 11GB integrated biomedical database. This skill is ideal for researchers and bioinformaticians who need to bridge the gap between high-level biological questions and technical data analysis across diverse domains like proteomics, genomics, and clinical diagnostics.

Key Features

Multi-step autonomous biological reasoning and task planning
89 GitHub stars
Automated code generation and execution for bioinformatics pipelines
Cross-domain problem solving from molecular biology to clinical tasks
Integrated access to ~11GB of curated biomedical databases and literature
Comprehensive support for CRISPR, RNA-seq, and GWAS analysis

Use Cases

Performing end-to-end single-cell RNA-seq analysis including clustering and annotation
Predicting ADMET properties and optimizing compounds for drug discovery
Designing genome-wide CRISPR screens and prioritizing gene candidates

About

Key Features

Multi-step autonomous biological reasoning and task planning
89 GitHub stars
Automated code generation and execution for bioinformatics pipelines
Cross-domain problem solving from molecular biology to clinical tasks
Integrated access to ~11GB of curated biomedical databases and literature
Comprehensive support for CRISPR, RNA-seq, and GWAS analysis

Use Cases

Performing end-to-end single-cell RNA-seq analysis including clustering and annotation
Predicting ADMET properties and optimizing compounds for drug discovery
Designing genome-wide CRISPR screens and prioritizing gene candidates