Related Experiment Video
Updated: Jun 26, 2026
Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
Published on: December 22, 2014
Prompt-based bioinformatic pipeline generation for a multi-step metaviral workflow
Pengchong Ma1, Haoze Zheng1, Weijun Yi2,3
1School of Computing, University of Nebraska Lincoln, Lincoln, NE 68588, United States.
Motivation:
The rapid evolution of bioinformatics tools and multi-step analytic procedure presents a challenge for building effective pipelines, particularly for researchers without extensive programming expertise. This study demonstrates that large language models (LLMs) hold strong potential for generating end-to-end bioinformatic pipelines through carefully crafted prompts, using a multi-step metaviral workflow as a representative example. Multiple LLMs were tested for their effectiveness, including OpenAI ChatGPT series, Anthropic Claude series, Google Gemini, Meta Llama, and DeepSeek.
Results:
Our results show that ChatGPT-4, ChatGPT-5, Claude 4.5, and Gemini 2.5 consistently outperform other LLMs in generating complete bioinformatic pipelines, with statistically significant success rates. These models also handle tool substitutions effectively. Simple prompt engineering and the inclusion of official documentation further enhance performance, especially for newer bioinformatic tools. While capabilities vary, all LLMs tested show potential for both pipeline generation and updates with our designed prompts and strategies.
Availability And Implementation:
All prompts are available in the paper. The examples are available in GitHub https://github.com/mpckkk/pBio.
