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arXiv · 2504.03976

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·Rishikumar Gopalan·Diego Gonzalez Lopez
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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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Dylan Riffle, Nima Shirooni, Cody He, Manush Murali, Sovit Nayak, Rishikumar Gopalan, Diego Gonzalez Lopez. 2025-04-04. OLAF: An Open Life Science Analysis Framework for Conversational Bioinformatics Powered by Large Language Models. https://arxiv.org/abs/2504.03976

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