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as soon as is submitted to ZB.
Data processing and automation in fourier transform mass spectrometry.
In: Fundamentals and Applications of Fourier Transform Mass Spectrometry. 2019. 133-185
Ultra-high resolution mass spectrometers produce large amount of
MS and MS/MS spectra, whose interpretations may not be easy even for
experts in this field. Noise among other interfering problems (such as
chemical background, side lobes, side bands, multiple harmonics) gather
in those spectra and make them complex. Moreover, all physical
characteristics (resolution, peak shape, signal to noise ratio
and signal intensity) of mass spectra originate and are actually
derived from their corresponding frequency spectra, which are generally
obtained by applying Fourier transform
to time domain detected transients. In this chapter, several data
processing techniques will be discussed for obtaining magnitude and
absorption modes frequency spectra and a review of most important mass
calibration equations will be discussed in great detail. De-noising,
peak alignment, sum formula calculations and batch processing of FTMS
spectra will also be discussed in this chapter. Moreover, automation of
FT-ICR mass spectrometers is reviewed here and the author illustrates in
this chapter a hand-on technical experience for achieving a successful
full automation of the 12 T FT-ICR mass spectrometer in
Helmholtz Zentrum München metabolomics research laboratory, which could
greatly enhance the productivity, by efficiently running in unattended
mode on 24 h basis. We selected over 135 related references in signal
processing and automation in an attempt to provide a comprehensive
guidance to mass spectrometry scientists.
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Publication type
Article: Edited volume or book chapter
Book Volume Title
Fundamentals and Applications of Fourier Transform Mass Spectrometry
Quellenangaben
Pages: 133-185
Non-patent literature
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Research Unit BioGeoChemistry and Analytics (BGC)