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Mass Spectrum01:23

Mass Spectrum

2.3K
A mass spectrum is the graphical representation of the relative abundance of the charged fragments in an analyte plotted against their mass-to-charge ratio (m/z). The plot's x axis represents the ratio of the mass of the charged fragment to the elementary charge it carries. The y axis of the plot represents the relative abundance of each charged species. The relative abundance is calculated from the signal intensity of each charged species recorded at the detector. The most intense signal...
2.3K
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

1.6K
An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a low-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.
To...
1.6K
Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

5.8K
Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass.  One common type of ionization, known as electrospray ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave...
5.8K
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

889
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...
889
Mass Spectrometers01:16

Mass Spectrometers

5.9K
This lesson details the instrumentation of a mass spectrometer—a physical instrument to perform mass spectrometry on analyte molecules and record the characteristic mass spectra. This is achieved via three chief functions:
5.9K
Mass Analyzers: Overview01:13

Mass Analyzers: Overview

807
The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
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Mass Spectrometry-Guided Genome Mining as a Tool to Uncover Novel Natural Products
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安定した質量スペクトル分類のためのリレーショナルグラフコンボリューションネットワーク

Raphaël La Rocca1, Anthony Cioppa2, Enrico Ferrarini3

  • 1Mass Spectrometry Laboratory, MolSys Research Unit, University of Liège, B4000, Liège, Belgium.

Journal of the American Society for Mass Spectrometry
|September 1, 2025
PubMed
まとめ
この要約は機械生成です。

この研究は,高解像度質量スペクトロメトリー (HRMS) 機能を活用した質量スペクトロメトリーイメージング (MSI) の新しいディープラーニングモデルを導入しています. リレーショナル・グラフ・コンボリューション・ネットワーク (R-GCN) は,化学的関係を考慮することでMSIデータの解釈とセグメンテーションを改善します.

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Analyzing Large Protein Complexes by Structural Mass Spectrometry
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Analyzing Large Protein Complexes by Structural Mass Spectrometry
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科学分野:

  • 分析化学
  • コンピュータ生物学
  • データサイエンス

背景:

  • マススペクトロメトリー画像 (MSI) データの解釈とセグメント化に優れている.
  • 現在の方法は,データセット特有の事前処理を必要とし,高解像度質量スペクトロメトリー (HRMS) の化学情報を過小利用しています.
  • HRMSは化学分析に不可欠な質量欠陥や質量差などの豊富な機能を提供します.

研究 の 目的:

  • HRMSの機能を効果的に利用するMSIのための新しいディープラーニングアーキテクチャを開発する.
  • 化学情報を明示的にコード化することでMSIデータの解釈とセグメンテーションを改善する.
  • MSI分析モデルの強度と解釈性を高める.

主な方法:

  • MSIのためのリレーショナル・グラフ・コンボリューション・ネットワーク (R-GCN) のアーキテクチャを提案した.
  • 化学的関係を捉えるために,質量欠陥と質量差をコードするグラフとしてスペクトルを表現した.
  • モデル解釈性のための統合クラスアクティベーションマッピング (CAM)

主要な成果:

  • R-GCNモデルは,さまざまなMSIデータセットで,従来のディープラーニングベースラインと比較して優れたパフォーマンスを示しました.
  • 質量シフトやイオン損失のような一般的なシグナル変数に対する強度を示した.
  • CAMは,特定の生物学的または空間的領域に関連した主要なイオンファミリーの識別を可能にしました.

結論:

  • R-GCNモデルは,既存の方法を上回る化学的に情報に基づいたMSI分析のアプローチを提供します.
  • この新しいアーキテクチャは,MSIデータからのサンプル組成の理解を高めます.
  • この方法は,MSIデータ分析のためのより解釈しやすく,より堅固なツールを提供します.