English(EN) RIVER: Evidence-guided multi-agent retrieval for enzyme--reaction discovery

新AI框架RIVER加速酶-反应发现

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-06 05:00

研究人员开发了RIVER，一个新颖的多智能体框架，用于酶-反应发现和注释。该系统集成了大型语言模型与专门的生化工具和外部知识资源，以整合来自各种来源的证据，包括反应化学、蛋白质序列和催化机制。RIVER旨在提高识别特定反应的候选酶以及找到给定酶催化的反应的准确性，在公共基准和文献构建的任务上表现优于现有方法。 AI

影响该框架可以通过提高酶和反应识别的效率和准确性来加速生物化学研究。

排序理由该集群包含一篇详细介绍用于科学发现任务的新AI框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yifan Chang, Yunze Li, Feifei Jiang, Juntao Wu, Xin Chen, Han Hu, Yucheng Wu, Wei Tang, Mingqian Ma, Wanli Ouyang, Kaipeng Zhang, Lei Bai, Hongting Tang, Feiran Li, Yuchen Ren · 2026-11-06 05:00

RIVER：基于证据的多智能体检索用于酶-反应发现

arXiv:2611.07757v1 Announce Type: new Abstract: Enzyme function annotation and the identification of candidate enzymes for a given reaction are essential steps in connecting genomic information to biochemical reaction networks. However, existing methods rely on sequence or struct…

本文如何被排名

报道来源 [1]

RIVER：基于证据的多智能体检索用于酶-反应发现

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