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相关概念视频

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and signal-to-noise ratio for the analyte. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.
Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called collision-induced...
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相关实验视频

Updated: Jun 2, 2025

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
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用于LC-MS的数据处理 非定向分析.

Mar Garcia-Aloy1, Johannes Rainer2, Pietro Franceschi3

  • 1Research and Innovation Centre, Fondazione E. Mach, Trento, Italy.

Methods in molecular biology (Clifton, N.J.)
|January 15, 2025
PubMed
概括

液体染色学-质谱学 (LC-MS) 的非目标代谢学需要先进的生物信息学来进行数据分析. 适当的数据预处理对于准确的结果和从复杂的实验数据中最大限度地获得洞察力至关重要.

关键词:
这些元数据是元数据.缺失的值是指缺失的值.峰值采摘 在采摘峰值采摘.预处理 预处理质量检查 质量检查保持时间校正 保持时间校正

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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.
  • 分析化学 分析化学

背景情况:

  • 使用液态染色学-质谱学 (LC-MS) 的非目标代谢学产生了复杂的数据集.
  • 提取有意义的生物信息需要复杂的生物信息学方法.

研究的目的:

  • 突出数据预处理在非目标LC-MS代谢学中的关键作用.
  • 强调需要仔细控制和优化预处理步骤的必要性.

主要方法:

  • 在LC-MS非目标实验中讨论数据预处理程序.
  • 专注于将原始数据转化为可用于统计分析的可用数据矩阵.

主要成果:

  • 数据预处理是知识提取的基本阶段.
  • 优化的预处理最大限度地提高了从代谢学研究中获得的信息产量.

结论:

  • 有效的数据预处理对于成功的非目标代谢学至关重要.
  • 仔细优化这些步骤是释放LC-MS数据全部潜力的关键.