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相关概念视频

Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

792
Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
792

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评估分析多类代谢学的机器学习方法

Yaguo Gong1, Wei Ding1, Panpan Wang2

  • 1State Key Laboratory of Quality Research in Chinese Medicine, School of Pharmacy, Macau University of Science and Technology, Macau 999078, China.

Journal of chemical information and modeling
|December 11, 2023
PubMed
概括

本研究审查和评估用于多类代谢学数据分析的机器学习方法. 绩效评估指导选择最佳方法组合,以获得复杂疾病研究中可靠的结果.

关键词:
这是分类分类的分类.数据分析数据分析数据分析归算是指指责一个人.机器学习是机器学习.代谢物的代谢物标志物标志物.多种类型的代谢学.规范化的正常化.绩效评价 绩效评价 绩效评价 绩效评价 绩效评价

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科学领域:

  • 代谢学 代谢学 代谢学
  • 生物信息学是一种生物信息学.
  • 机器学习 机器学习

背景情况:

  • 多类代谢学对于理解复杂的疾病,生活方式和治疗效果至关重要.
  • 数据分析涉及诸如归算,规范化和分类等多个步骤,每一步都提供了众多机器学习方法的选择.
  • 缺乏全面的评估阻碍了最佳方法选择,以获得可靠的分析结果.

研究的目的:

  • 提供机器学习方法在多类代谢学数据处理中使用的详细审查.
  • 在不同的数据处理步骤中评估各种机器学习方法的性能.
  • 引导研究人员选择适当的方法组合,以便进行稳定可靠的多类代谢分析.

主要方法:

  • 审查了用于数据过,缺失值赋值,规范化,标记物识别和分类的机器学习方法.
  • 通过Procrustes统计形状分析 (PSS) 和正常化根-平均平方误差 (NRMSE) 评估了12种归算方法.
  • 评估了17种使用聚合中位数绝对偏差 (PMAD) 的规范化方法,使用相对加权一致性 (CWrel) 的标记物识别方法以及使用曲线下面积 (AUC) 的9种分类方法.

主要成果:

  • 使用性能指标 (PSS,NRMSE,PMAD,CWrel,AUC) 来比较不同的机器学习方法.
  • 该研究提供了对基准多类代谢学数据集中的各种方法的经验评估.
  • 评估了特定方法在归算,规范化,标记物识别和分类任务中的有效性.

结论:

  • 机器学习方法的性能评估对于在最终数据分析之前选择最佳组合至关重要.
  • 本书提供了详细的描述和评估,以加强对多类代谢数据的分析.
  • 这些发现旨在提高多类代谢学研究结果的可复制性和可靠性.