OLAF: An Open Life Science Analysis Framework for Conversational Bioinformatics Powered by Large Language Models

Dylan Riffle, Nima Shirooni, Cody He, Manush Murali, Sovit Nayak +2 more
4/4/2025
q-bio.QMcs.AIq-bio.GN

No official code found. Best implementation: OpenTechBio/Olaf (25 stars, last commit 2025-09-16).

Abstract

OLAF (Open Life Science Analysis Framework) is an open-source platform that enables researchers to perform bioinformatics analyses using natural language. By combining large language models (LLMs) with a modular agent-pipe-router architecture, OLAF generates and executes bioinformatics code on real scientific data, including formats like .h5ad. The system includes an Angular front end and a Python/Firebase backend, allowing users to run analyses such as single-cell RNA-seq workflows, gene annotation, and data visualization through a simple web interface. Unlike general-purpose AI tools, OLAF integrates code execution, data handling, and scientific libraries in a reproducible, user-friendly environment. It is designed to lower the barrier to computational biology for non-programmers and support transparent, AI-powered life science research.

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Code Implementations(1)

OpenTechBio/OlafCommunity100%

The Open Life Science Analysis Platform

258HTML, SCSSMar 20, 20251 years ago

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Cite this paper

@article{riffle2025olaf,
  title  = {OLAF: An Open Life Science Analysis Framework for Conversational Bioinformatics Powered by Large Language Models},
  author = {Dylan Riffle and Nima Shirooni and Cody He and Manush Murali and Sovit Nayak and Rishikumar Gopalan and Diego Gonzalez Lopez},
  year   = {2025},
  eprint = {2504.03976},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2504.03976v2}
}

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