打造可复现的基因组模型评测平台，统一数据与评估标准
OmniGenBench: A Modular Platform for Reproducible Genomic Foundation Models Benchmarking
- 构建模块化平台，整合数据、模型、评测与可解释性层
- 支持31个开源模型一键评测，覆盖5大基准套件
- 解决数据透明、模型互操作等复现难题，适合基因组AI研究者
生命代码——自生命起源以来嵌入DNA和RNA基因组中的信息，通过基因组建模有望深刻影响人类与生态系统。基因组基础模型（Genomic Foundation Models, GFMs）成为破解基因组奥秘的变革性方法。随着GFMs规模扩大并重塑人工智能驱动的基因组学格局，领域亟需严谨且可复现的评估体系。我们提出OmniGenBench，一个模块化基准评测平台，旨在统一跨GFMs的数据、模型、评测与可解释性层级。该平台支持对任意GFM进行标准化的一键式评估，覆盖五大基准套件，并无缝集成超过31个开源模型。通过自动化流水线与社区可扩展功能，平台有效应对数据透明性、模型互操作性、评测碎片化及黑箱可解释性等关键复现挑战。OmniGenBench致力于成为可复现基因组人工智能研究的基础设施，推动基因组尺度建模时代的可信发现与协同创新。
原文摘要 · Abstract (English)
The code of nature, embedded in DNA and RNA genomes since the origin of life, holds immense potential to impact both humans and ecosystems through genome modeling. Genomic Foundation Models (GFMs) have emerged as a transformative approach to decoding the genome. As GFMs scale up and reshape the landscape of AI-driven genomics, the field faces an urgent need for rigorous and reproducible evaluation. We present OmniGenBench, a modular benchmarking platform designed to unify the data, model, benchmarking, and interpretability layers across GFMs. OmniGenBench enables standardized, one-command evaluation of any GFM across five benchmark suites, with seamless integration of over 31 open-source models. Through automated pipelines and community-extensible features, the platform addresses critical reproducibility challenges, including data transparency, model interoperability, benchmark fragmentation, and black-box interpretability. OmniGenBench aims to serve as foundational infrastructure for reproducible genomic AI research, accelerating trustworthy discovery and collaborative innovation in the era of genome-scale modeling.
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