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Related Concept Videos

Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. 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...
Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

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 electron 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 behind a...
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

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...
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

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 soft-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...
Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
One type of fragmentation pattern is the cleavage of a single bond in the molecular ion. The cleavage leads to a radical and a cation. The cleavage can occur at...
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For example, the mass of helium...

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Updated: Jun 28, 2026

Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry (CCMS)
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Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry (CCMS)

Published on: December 20, 2010

mspire: mass spectrometry proteomics in Ruby.

John T Prince1, Edward M Marcotte

  • 1Institute for Cellular and Molecular Biology, University of Texas, Austin, TX 78712, USA.

Bioinformatics (Oxford, England)
|October 22, 2008
PubMed
Summary
This summary is machine-generated.

The mspire software library, written in Ruby, offers efficient data handling for mass spectrometry proteomics. It provides fast readers and converters for complex datasets, improving analysis speed and memory usage.

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

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Last Updated: Jun 28, 2026

Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry (CCMS)
17:12

Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry (CCMS)

Published on: December 20, 2010

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Proteomics

Background:

  • Mass spectrometry-based proteomics generates large, complex datasets.
  • Efficient data analysis is crucial for extracting meaningful biological insights.
  • Existing scripting language tools may face challenges with speed and memory demands.

Purpose of the Study:

  • To introduce 'mspire', a software library designed for efficient analysis of mass spectrometry-based proteomics data.
  • To address the computational challenges posed by large and complex proteomics datasets.
  • To provide tools for common proteomics data workflows.

Main Methods:

  • Development of the 'mspire' software library in the Ruby programming language.
  • Implementation of quick and memory-efficient readers for standard XML proteomics formats.
  • Inclusion of converters for intermediate file types in proteomics spectral-identification workflows, such as the Bioworks .srf format.
  • Integration of modules for calculating peptide false identification rates.

Main Results:

  • 'mspire' provides fast and memory-efficient data handling for proteomics.
  • The library facilitates common proteomics data processing tasks.
  • Modules for false identification rate calculation enhance data reliability.

Conclusions:

  • 'mspire' offers a valuable solution for accelerating and optimizing mass spectrometry-based proteomics data analysis.
  • The Ruby-based library effectively manages large datasets, improving computational efficiency.
  • 'mspire' supports critical steps in proteomics workflows, including data conversion and quality assessment.