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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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...
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...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...
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 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...
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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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

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Cloud parallel processing of tandem mass spectrometry based proteomics data.

Yassene Mohammed1, Ekaterina Mostovenko, Alex A Henneman

  • 1Biomolecular Mass Spectrometry Unit, Department of Parasitology, Leiden University Medical Center, The Netherlands. y.mohammed@lumc.nl

Journal of Proteome Research
|August 25, 2012
PubMed
Summary
This summary is machine-generated.

This study presents a novel data decomposition method to parallelize mass spectrometry data analysis. This approach accelerates proteomics research by enabling faster identification of tandem mass spectra using cloud computing.

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Area of Science:

  • Proteomics
  • Computational Biology
  • Bioinformatics

Background:

  • Mass spectrometry-based proteomics generates large datasets that challenge current data analysis capabilities.
  • Existing data analysis workflows involve multiple steps with diverse software, algorithms, and data formats, hindering efficiency.
  • The speed of mass spectral search engines has not kept pace with the increasing rate of data acquisition.

Purpose of the Study:

  • To develop a general method for parallelizing tandem mass spectra identification.
  • To address the computational bottleneck in large-scale proteomics data analysis.
  • To enable faster and more efficient processing of mass spectrometry data.

Main Methods:

  • A data decomposition strategy is proposed to introduce parallelism without altering existing search engines.
  • Two algorithms for decomposing mzXML files and recomposing pepXML files are introduced.
  • Cloud computing and scientific workflow engines are utilized for computational power and automation.

Main Results:

  • The data decomposition method effectively parallelizes tandem mass spectra identification.
  • The approach is compatible with various search engines, including sequence database and spectral library searches.
  • Three scientific workflows for parallel database and spectral library searches were demonstrated.

Conclusions:

  • Data decomposition offers a simpler and effective strategy for parallelizing proteomics data analysis.
  • Leveraging cloud computing and workflow engines significantly accelerates data analysis in proteomics.
  • This method enhances the scalability and efficiency of mass spectrometry data processing.