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Protein Identification from Tandem Mass Spectra by Database Searching

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Protein Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1558))

Abstract

Protein identification from tandem mass spectra is one of the most versatile and widely used proteomics workflows, able to identify proteins, characterize post-translational modifications, and provide semiquantitative measurements of relative protein abundance. This manuscript describes the concepts, prerequisites, and methods required to analyze a tandem mass spectrometry dataset in order to identify its proteins, by using a tandem mass spectrometry search engine to search protein sequence databases. The discussion includes instructions for extraction, preparation, and formatting of spectral datafiles, selection of appropriate search parameter settings, and basic interpretation of the results.

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Notes

  1. 1.

    See http://tools.proteomecenter.org/wiki/index.php?title=Formats:mzXML.

  2. 2.

    See http://proteowizard.sourceforge.net.

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Author information

Authors and Affiliations

  1. Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC, 20007, USA

    Nathan J. Edwards

Authors
  1. Nathan J. Edwards
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Correspondence to Nathan J. Edwards .

Editor information

Editors and Affiliations

  1. Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, USA

    Cathy H. Wu

  2. Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, USA

    Cecilia N. Arighi

  3. Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, District of Columbia, USA

    Karen E. Ross

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Edwards, N.J. (2017). Protein Identification from Tandem Mass Spectra by Database Searching. In: Wu, C., Arighi, C., Ross, K. (eds) Protein Bioinformatics. Methods in Molecular Biology, vol 1558. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6783-4_17

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  • DOI: https://doi.org/10.1007/978-1-4939-6783-4_17

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6781-0

  • Online ISBN: 978-1-4939-6783-4

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