Proteomics profiles from mass spectrometry

Inge Koch, Peter Hoffmann, J. S. Marron

Research output: Contribution to journalArticle

10 Citations (Scopus)


Proteomics is a rapidly growing research area within bioinformatics which focuses on quantification of peptide concentrations and on the identification of proteins and peptides. In quantitative proteomics the identification of biomarkers from peptide concentrations is important for diagnostic purposes and treatment of diseases.

The goal of this paper is to facilitate research in this area, by providing a test bed for comparison of 1D curve registration methods. This is done in a novel way, by providing not only curves, but also an answer key as to how the peaks should align. In the following papers a number of approaches to this problem are given, and the answer key provides unusually useful insights into how the methods compare.

For this reason, we consider proteomics mass spectrometry profiles which are part of a larger study into the identification of biomarkers in Acute Myeloid Leukaemia (AML). For these profiles large ion counts result in large peaks, but these peaks may occur at different retention times for dif- ferent profiles. The first step in the quantification of peptides in proteomics profiles is the alignment of the 1D curves of total ion count (TIC).

The paper includes a description of proteomics mass spectrometry pro- filing, and considers profiles from five patients with AML. It outlines the preprocessing steps we applied to the multiple TIC samples from each patient, and introduces the reference peptides. The retention times of the reference peptides are known for each profile, and using these times as an answer key makes the 1D TIC curves a particularly informative test bed for curve registration.

Original languageEnglish
Pages (from-to)1703-1713
Number of pages11
JournalElectronic Journal of Statistics
Issue number1
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Fingerprint Dive into the research topics of 'Proteomics profiles from mass spectrometry'. Together they form a unique fingerprint.

Cite this