What domains of biology does Biomni support?

Biomni supports a wide range of domains including genomics, proteomics, molecular biology, clinical analysis, and drug discovery.

Is Biomni's code execution safe?

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

Can Biomni perform single-cell RNA-seq analysis?

Yes, it can perform QC, filtering, clustering, cell type annotation, and differential expression analysis autonomously using natural language queries.

Does Biomni require its own data source?

Biomni comes with an integrated 11GB data lake containing gene databases, protein structures, clinical datasets, and literature indices which it downloads on first use.

Which LLMs are compatible with Biomni?

It is optimized for Anthropic Claude (Sonnet and Opus), but also supports OpenAI GPT-4, Google Gemini, Llama 3 via Groq, and AWS Bedrock.

Biomni Biomedical AI Agent

Name: Biomni Biomedical AI Agent
Author: Activer007

byActiver007

Ciencia de Datos y ML

Executes autonomous multi-step research tasks across genomics, drug discovery, and clinical analysis using integrated biomedical databases.

Acerca de

Biomni is a comprehensive framework from Stanford’s SNAP lab designed to automate complex biomedical research. It leverages LLM reasoning to decompose tasks, generate and execute analysis code, and retrieve data from over 11GB of integrated biomedical knowledge sources. Whether you are designing CRISPR screens, analyzing single-cell RNA-seq data, or predicting drug ADMET properties, Biomni provides a unified interface for cross-domain problem-solving and literature synthesis, significantly accelerating the biological discovery process.

Características Principales

Cross-domain support for genomics, proteomics, drug discovery, and clinical tasks
0 GitHub stars
Multi-step autonomous biological reasoning and task decomposition
Built-in evaluation framework for benchmarking agent performance on biomedical tasks
Access to 11GB of integrated biomedical databases including Gene, Protein, and Clinical data
Dynamic Python code generation and execution for data pipelines

Casos de Uso

Performing end-to-end single-cell RNA-seq analysis and cell type annotation
Designing genome-wide CRISPR knockout screens and gene prioritization
Predicting ADMET properties and identifying targets for drug discovery

Acerca de

Características Principales

Cross-domain support for genomics, proteomics, drug discovery, and clinical tasks
0 GitHub stars
Multi-step autonomous biological reasoning and task decomposition
Built-in evaluation framework for benchmarking agent performance on biomedical tasks
Access to 11GB of integrated biomedical databases including Gene, Protein, and Clinical data
Dynamic Python code generation and execution for data pipelines

Casos de Uso

Performing end-to-end single-cell RNA-seq analysis and cell type annotation
Designing genome-wide CRISPR knockout screens and gene prioritization
Predicting ADMET properties and identifying targets for drug discovery