微生物发现:一个知识图启用的人工智能框架,用于识别微生物的无机纳米材料生物合成
Ludi Wang1,2, Hexing Han3, Yufeng Liu1
1Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|January 25, 2026
概括
一个AI框架,MicrobeDiscover,加速了微生物的发现,以实现可持续的纳米材料 (NM) 合成. 它成功地确定了用于新型三金属NM生产的微生物,提高了效率.
科学领域:
- 微生物学 微生物学
- 材料科学 材料科学 材料科学
- 人工智能的人工智能
背景情况:
- 微生物合成纳米材料 (NM) 提供了一种可持续的方法,但由于已知微生物-NM组合的数量有限而受到限制.
- 目前的研究依赖于低效的实证方法来识别合适的微生物.
研究的目的:
- 开发一个基于人工智能的框架,MicrobeDiscover,以有效识别能够合成NMs的微生物.
- 扩大微生物NM合成的范围,超出之前报告的组合.
主要方法:
- 开发了MicrobeDiscover,这是一个集成微生物,NM及其相互作用的AI框架,使用知识图.
- 该框架将微生物学和材料科学结合起来,用于强大的选和预测建模.
- 通过使用人工智能识别的微生物试图合成三金属NM的验证预测.
主要成果:
- 微生物发现从其前20个预测中获得了80.77%的成功率来识别合适的微生物.
- 正如框架所预测的那样,使用*Shewanella oneidensis* MR-1成功合成了新的三金属NM.
- 证明了该框架能够预测微生物合成以前在生物合成环境中未报告的NMs的能力.
结论:
- MicrobeDiscover显著提高了对NM合成的选微生物的效率.
- 人工智能框架有助于发现新的微生物-NM组合和可控制的NM合成.
- 这种方法有望推动可持续的纳米材料生产和微生物材料混合系统.
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