Chapter

Modern Proteomics – Sample Preparation, Analysis and Practical Applications

Volume 919 of the series Advances in Experimental Medicine and Biology pp 227-235

Date:

Visualization, Inspection and Interpretation of Shotgun Proteomics Identification Results

  • Ragnhild R. LereimAffiliated withProteomics Unit, Department of Biomedicine, University of BergenKG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical Medicine, University of BergenNorwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University
  • , Eystein OvelandAffiliated withKG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical Medicine, University of BergenNorwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland UniversityDepartment of Clinical Medicine, University of Bergen
  • , Frode S. BervenAffiliated withProteomics Unit, Department of Biomedicine, University of BergenKG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical Medicine, University of BergenNorwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University
  • , Marc VaudelAffiliated withProteomics Unit, Department of Biomedicine, University of Bergen
  • , Harald BarsnesAffiliated withProteomics Unit, Department of Biomedicine, University of Bergen Email author 

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Abstract

Shotgun proteomics is a high throughput technique for protein identification able to identify up to several thousand proteins from a single sample. In order to make sense of this large amount of data, proteomics analysis software is needed, aimed at making the data intuitively accessible to beginners as well as experienced scientists. This chapter provides insight on where to start when analyzing shotgun proteomics data, with a focus on explaining the most common pitfalls in protein identification analysis and how to avoid them. Finally, the move to seeing beyond the list of identified proteins and to putting the results into a bigger biological context is discussed.

Keywords

Protein identification Visualization Protein annotation Validation