Chapter

Proteogenomics

Volume 926 of the series Advances in Experimental Medicine and Biology pp 65-75

Date:

Using Proteomics Bioinformatics Tools and Resources in Proteogenomic Studies

  • Marc VaudelAffiliated withProteomics Unit, Department of Biomedicine, University of BergenKG Jebsen Center for Diabetes Research, Department of Clinical Science, University of BergenCenter for Medical Genetics and Molecular Medicine, Haukeland University Hospital Email author 
  • , Harald BarsnesAffiliated withProteomics Unit, Department of Biomedicine, University of BergenKG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen
  • , Helge RæderAffiliated withKG Jebsen Center for Diabetes Research, Department of Clinical Science, University of BergenDepartment of Pediatrics, Haukeland University Hospital
  • , Frode S. BervenAffiliated withProteomics Unit, Department of Biomedicine, University of Bergen

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Abstract

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.

Keywords

Proteogenomics Proteomics Bioinformatics