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English(EN) TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval

AI 推动生物学酶-反应检索发展

两篇新研究论文介绍了计算生物学中用于酶-反应检索的先进 AI 框架。第一个框架 TIGER 使用蛋白质到文本生成来创建通用的表示,以连接酶和生化反应,从而提高泛化能力和鲁棒性。第二个框架是一个多对齐对比学习框架,它将酶-反应兼容性与域内关系和几何一致性联合建模,从而提高检索准确性和功能注释。 AI

影响 这些 AI 框架为酶发现、反应注释和生物催化剂设计提供了改进的工具,推动了计算生物学研究。

排序理由 两篇学术论文展示了针对特定科学领域的 AI 新方法。

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

AI 推动生物学酶-反应检索发展

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两篇学术论文展示了针对特定科学领域的 AI 新方法。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yuhang Zhang, Keyan Ding, Peilin Chen, Han Liu, Can Lin, Ruixi Chen, Shiqi Wang, Qi Song ·

    TIGER:文本信息通用酶-反应检索

    arXiv:2605.24489v1 Announce Type: new Abstract: Enzyme-reaction retrieval is a fundamental problem in computational biology, underpinning enzyme characterization, reaction mechanism elucidation, and the rational design of metabolic pathways and biocatalysts. As a bidirectional ta…

  2. arXiv cs.LG TIER_1 English(EN) · Gengmo Zhou, Feng Yu, Wenda Wang, Zhifeng Gao, Guolin Ke, Zhewei Wei, Zhen Wang ·

    用于酶-反应检索的多对齐对比学习

    arXiv:2512.08508v2 Announce Type: replace-cross Abstract: Identifying enzymes that catalyze target biochemical reactions is a key step in computational enzyme discovery and biocatalyst design. Recent representation-learning methods formulate this problem as enzyme--reaction match…