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bioRxiv · 10.64898/2026.05.05.723092

PromptBio-Bench: Benchmarking LLM-based Bioinformatics Agents for End-to-End Data Analysis

Guo, W.·Zhang, M.·Han, B.·Ma, Y.·Leng, Y.·Hebbar, S.·Zhou, X.·Gu, W.·Yang, X.·Dhar, S.
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Abstract

Large language model (LLM)-based agents hold transformative potential for automating bioinformatics workflows; however, systematic evaluations of their capabilities remain limited, hindering a clear assessment of their readiness for real-world application. We introduce PromptBio-Bench, a comprehensive evaluation suite of 244 expert-curated tasks spanning bioinformatics and data science at varied difficulty levels, and an evaluation framework for structured file comparison and scoring against expert reference answer files. Evaluation of three state-of-the-art bioinformatics agents revealed comparable performance between Biomni and ToolsGenie, with all agents showing a marked decline in accuracy as task difficulty increased. As foundation models and agent frameworks continue to evolve, PromptBio-Bench provides a valuable benchmark infrastructure for systematically tracking progress in agentic bioinformatics.

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Guo, W., Zhang, M., Han, B., Ma, Y., Leng, Y., Hebbar, S., Zhou, X., Gu, W., Yang, X., Dhar, S.. 2026-05-08. PromptBio-Bench: Benchmarking LLM-based Bioinformatics Agents for End-to-End Data Analysis. https://doi.org/10.64898/2026.05.05.723092

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