Computational and Statistical Methods for High-Throughput Mass Spectrometry-Based PTM Analysis

Veit Schwämmle; Marc Vaudel

doi:10.1007/978-1-4939-6783-4_21

Computational and Statistical Methods for High-Throughput Mass Spectrometry-Based PTM Analysis

Methods Mol Biol. 2017:1558:437-458. doi: 10.1007/978-1-4939-6783-4_21.

Authors

Veit Schwämmle¹, Marc Vaudel²

Affiliations

¹ Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230, Odense, Denmark. veits@bmb.sdu.dk.
² Proteomics Unit, Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020, Bergen, Norway.

PMID: 28150251
DOI: 10.1007/978-1-4939-6783-4_21

Abstract

Cell signaling and functions heavily rely on post-translational modifications (PTMs) of proteins. Their high-throughput characterization is thus of utmost interest for multiple biological and medical investigations. In combination with efficient enrichment methods, peptide mass spectrometry analysis allows the quantitative comparison of thousands of modified peptides over different conditions. However, the large and complex datasets produced pose multiple data interpretation challenges, ranging from spectral interpretation to statistical and multivariate analyses. Here, we present a typical workflow to interpret such data.

Keywords: Bioinformatics; Post-translational modifications (PTMs); Proteomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology / methods*
Data Interpretation, Statistical*
Data Mining / methods*
Databases, Protein
Mass Spectrometry*
Protein Processing, Post-Translational*
Proteins* / chemistry
Proteins* / metabolism
Proteomics / methods*
Search Engine
Software
User-Computer Interface
Web Browser

Substances

Proteins