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English(EN) PlantBGC: Transformer for Plant BGC Discovery via Label-Free Domain Adaptation and Weak Supervision

AI工具PlantBGC增强植物生物合成基因簇的发现

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了PlantBGC，一种新颖的、由AI驱动的工具，用于发现植物生物合成基因簇（BGC）。PlantBGC使用了一个仅编码器的Transformer模型，该模型在微生物BGC上进行训练，并通过无标签域自适应将其应用于植物基因组。与plantiSMASH等现有方法相比，这种方法显著提高了在植物中已知BGC的恢复率，并提供了更准确的边界识别。该系统还结合了来自GO和KEGG通路的弱监督信号以减少假阳性，展示了植物BGC发现效率和准确性的显著提升。 AI

影响 增强了AI在生物学研究中的作用，有望加速药物发现和对植物代谢组学的理解。

排序理由 该集群描述了一篇详细介绍用于生物学发现的新型AI模型的研究论文。

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AI工具PlantBGC增强植物生物合成基因簇的发现

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Yuhan Zhao, Nidhi Grover, Zhishan Guo, Ning Sui ·

    PlantBGC：通过无标记域自适应和弱监督实现植物BGC发现的Transformer

    arXiv:2607.27258v1 Announce Type: cross Abstract: Plant biosynthetic gene clusters (BGCs) encode specialized-metabolite pathways, yet curated plant BGC labels remain scarce, hindering supervised discovery at genome scale. Existing plant BGC mining tools are largely signature- and…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    PlantBGC：通过无标记域自适应和弱监督实现植物BGC发现的Transformer

    Plant biosynthetic gene clusters (BGCs) encode specialized-metabolite pathways, yet curated plant BGC labels remain scarce, hindering supervised discovery at genome scale. Existing plant BGC mining tools are largely signature- and rule-driven and do not fully leverage recent adva…

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