Using Proteomics Bioinformatics Tools and Resources in Proteogenomic Studies

  • Marc Vaudel
  • Harald Barsnes
  • Helge Ræder
  • Frode S. Berven
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 926)


Proteogenomic studies ally the omic fields related to gene expression into a combined approach to improve the characterization of biological samples. Part of this consists in mining proteomics datasets for non-canonical sequences of amino acids. These include intergenic peptides, products of mutations, or of RNA editing events hypothesized from genomic, epigenomic, or transcriptomic data. This approach poses new challenges for standard peptide identification workflows. In this chapter, we present the principles behind the use of peptide identification algorithms and highlight the major pitfalls of their application to proteogenomic studies.


Proteogenomics Proteomics Bioinformatics 



H.B. and H.R are supported by Bergen Forskningsstiftelse, and H.R. is further supported by Novo Nordisk Fonden and Western Norway Regional Health Authority. F.B. is supported by the Kristian Gerhard Jebsen foundation.

Conflict of Interest

The authors declare no competing financial interests.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Marc Vaudel
    • 1
    • 2
    • 3
  • Harald Barsnes
    • 1
    • 2
  • Helge Ræder
    • 2
    • 4
  • Frode S. Berven
    • 1
  1. 1.Proteomics Unit, Department of BiomedicineUniversity of BergenBergenNorway
  2. 2.KG Jebsen Center for Diabetes Research, Department of Clinical ScienceUniversity of BergenBergenNorway
  3. 3.Center for Medical Genetics and Molecular MedicineHaukeland University HospitalBergenNorway
  4. 4.Department of PediatricsHaukeland University HospitalBergenNorway

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