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Updated: Jun 4, 2025

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow
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Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

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不确定性量化和标记不可靠的预测,用于预测小分子的质谱相关性质,使用机器学习

Dmitriy D Matyushin1, Ivan A Burov1, Anastasia Yu Sholokhova1

  • 1A.N. Frumkin Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences, 31 Leninsky Prospect, GSP-1, 119071 Moscow, Russia.

International journal of molecular sciences
|December 17, 2024
PubMed
概括

这项研究引入了一种新的方法,用于估计分子识别中的预测不确定性. 通过结合集合模型的传播,分子相似性和数据聚类,研究人员可以更好地评估代谢学和染色学预测的可靠性.

关键词:
碰撞横截面的截面.深度学习是一种深度学习.代谢生物组的代谢生物组保留指数的保持指数.保留时间 保留时间不确定性估计估计的不确定性

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