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Related Concept Videos

Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

6.9K
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...
6.9K
Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

4.2K
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...
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Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

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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...
1.1K
Mass Spectrometers01:16

Mass Spectrometers

7.1K
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:
7.1K
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

1.8K
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...
1.8K
Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

1.6K
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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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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mspack: efficient lossless and lossy mass spectrometry data compression.

Felix Hanau1, Hannes Röst2, Idoia Ochoa3,4

  • 1Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.

Bioinformatics (Oxford, England)
|September 3, 2021
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Summary
This summary is machine-generated.

A new compression algorithm, mspack, significantly reduces file sizes for mass spectrometry (MS) data. It offers superior lossless and lossy compression for proteomics and metabolomics, lowering storage costs.

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Area of Science:

  • Proteomics and Metabolomics
  • Computational Biology
  • Data Compression

Background:

  • Mass spectrometry (MS) data is rapidly growing, increasing storage costs.
  • Existing compression algorithms like MassComp and MSNumpress do not fully exploit data redundancy across scans.
  • There is a need for efficient compression methods for MS data in proteomics and metabolomics.

Purpose of the Study:

  • Introduce mspack, a novel compression algorithm for MS data.
  • Exploit redundancy across scans for improved compression ratios.
  • Support both lossless and lossy compression for mzML and mzXML formats.

Main Methods:

  • mspack applies preprocessing lossless and optional lossy transforms.
  • Configurable error tolerance for lossy compression.
  • Utilizes general-purpose compressors like gzip or bsc for final compression.

Main Results:

  • mspack achieves 76% smaller file sizes for lossless and 94% for lossy compression on average.
  • Lossless mspack outperforms MassComp by 10-60%.
  • Lossy mspack offers 36-60% better compression than MSNumpress at comparable accuracy.

Conclusions:

  • mspack provides significant file size reduction for MS data.
  • The algorithm is effective for both lossless and lossy compression scenarios.
  • It offers a valuable solution for managing large MS datasets in scientific research.