利用多组学和机器学习破解抗微生物药物耐药性问题。
Unlocking antimicrobial resistance with multiomics and machine learning.
作者信息
Ghosh Abhirupa, Vang Charmie K, Brenner Evan P, Ravi Janani
机构信息
Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA.
Department of Biomedical Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA.
出版信息
Trends Microbiol. 2025 May 26. doi: 10.1016/j.tim.2025.04.017.
Abstract
The global antimicrobial resistance (AMR) emergency is driven by complex and evolving molecular mechanisms. Cutting-edge machine learning methods and multiomics technologies can help to combat this crisis by predicting novel AMR biomarkers and outcomes with unprecedented precision and speed, offering critical insights into the molecular underpinnings of AMR.
摘要
全球抗菌药物耐药性（AMR）危机是由复杂且不断演变的分子机制驱动的。前沿的机器学习方法和多组学技术能够以前所未有的精度和速度预测新的AMR生物标志物及结果，从而有助于应对这一危机，为AMR的分子基础提供关键见解。
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