arXiv:2512.24733cs.CL2025-12被引 1

构建首个多组学通路机制解析基准,评测大模型从文献推断分子互作的能力。

BIOME-Bench: A Benchmark for Biomolecular Interaction Inference and Multi-Omics Pathway Mechanism Elucidation from Scientific Literature

  • 通过四阶段流程构建跨文献的多组学分析基准数据集
  • 现有大模型在细粒度分子关系识别上表现不佳
  • 适合生物信息学、AI制药与可解释性研究者参考

多组学研究常依赖通路富集分析(PE)来解读分子变化,但现有通路资源存在注释滞后、功能冗余和对分子状态敏感性不足等结构性缺陷。尽管近期尝试用大语言模型(LLMs)改进PE分析,但缺乏标准化的端到端多组学通路机制解析评估基准,导致评估局限于小规模人工标注数据或特定案例,阻碍了可复现的进展。为此,我们提出BIOME-Bench,采用严谨的四阶段工作流,用于评估大模型在两个核心能力上的表现:生物分子互作推断与端到端多组学通路机制阐明。我们开发了针对两项任务的评估协议,并在多个主流大模型上开展全面实验。结果表明,当前模型在多组学分析中仍存在显著不足,难以可靠区分细粒度的生物分子关系类型,也难以生成忠实且稳健的通路级机制解释。

原文摘要 · Abstract (English)

Multi-omics studies often rely on pathway enrichment to interpret heterogeneous molecular changes, but pathway enrichment (PE)-based workflows inherit structural limitations of pathway resources, including curation lag, functional redundancy, and limited sensitivity to molecular states and interventions. Although recent work has explored using large language models (LLMs) to improve PE-based interpretation, the lack of a standardized benchmark for end-to-end multi-omics pathway mechanism elucidation has largely confined evaluation to small, manually curated datasets or ad hoc case studies, hindering reproducible progress. To address this issue, we introduce BIOME-Bench, constructed via a rigorous four-stage workflow, to evaluate two core capabilities of LLMs in multi-omics analysis: Biomolecular Interaction Inference and end-to-end Multi-Omics Pathway Mechanism Elucidation. We develop evaluation protocols for both tasks and conduct comprehensive experiments across multiple strong contemporary models. Experimental results demonstrate that existing models still exhibit substantial deficiencies in multi-omics analysis, struggling to reliably distinguish fine-grained biomolecular relation types and to generate faithful, robust pathway-level mechanistic explanations.

多组学大模型通路分析生物信息

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