Prompt-Based Bioinformatic Pipeline Generation for a Multi-Step Metaviral Workflow

Authors: Pengchong Ma, Haoze Zheng, Weijun Yi, Li Ma, Brandi Sigmon, Karrie A Weber, Gangqing Hu, Qiuming Yao

Published in: Bioinformatics Advances, (2025)

DOI: doi.org/10.1093/bioadv/vbaf308

Abstract:

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.