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.
@article{arxiv.2504.03976,
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},
journal= {arXiv preprint arXiv:2504.03976},
year = {2025}
}