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Mass spectrometry and computational proteomics

Part 4. Bioinformatics

4.5. Computational Methods for High-throughput Genetic Analysis: Expression Profiling

Introductory Review

  1. Vineet Bafna1,
  2. Knut Reinert2

Published Online: 15 OCT 2004

DOI: 10.1002/047001153X.g405101

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Bafna, V. and Reinert, K. 2004. Mass spectrometry and computational proteomics. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.5:51.

Author Information

  1. 1

    University of California, San Diego, CA, USA

  2. 2

    Free University Berlin, Berlin, Germany

Publication History

  1. Published Online: 15 OCT 2004


Mass Spectrometry is the tool of choice for proteomics, with applications to peptide sequencing, protein structure prediction, protein–protein interactions, and many others. Continued improvements in instrumentation and computational technologies will only help accelerate this trend. A short overview of algorithms for interpreting mass spectrometry (MS) data is provided. This overview is not intended as an introduction to the technology itself or to proteomics. Instead, an abstract overview of MS data is presented in order to describe key algorithmic ideas required for its interpretation. Three proteomic applications are considered: protein identification, protein interactions, and differential analysis of protein expression.


  • de novo sequencing;
  • dynamic programming;
  • electrospray;
  • MALDI;
  • mass spectrometry;
  • tandem mass spectrometry;
  • proteomics