OLAF: An Open Life Science Analysis Framework for Conversational Bioinformatics Powered by Large Language Models
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913788254486528 |
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| author | Riffle, Dylan Shirooni, Nima He, Cody Murali, Manush Nayak, Sovit Gopalan, Rishikumar Lopez, Diego Gonzalez |
| author_facet | Riffle, Dylan Shirooni, Nima He, Cody Murali, Manush Nayak, Sovit Gopalan, Rishikumar Lopez, Diego Gonzalez |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_03976 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | OLAF: An Open Life Science Analysis Framework for Conversational Bioinformatics Powered by Large Language Models Riffle, Dylan Shirooni, Nima He, Cody Murali, Manush Nayak, Sovit Gopalan, Rishikumar Lopez, Diego Gonzalez Quantitative Methods Artificial Intelligence Genomics 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. |
| title | OLAF: An Open Life Science Analysis Framework for Conversational Bioinformatics Powered by Large Language Models |
| topic | Quantitative Methods Artificial Intelligence Genomics |
| url | https://arxiv.org/abs/2504.03976 |