Journalartikel

Jahr der Veröffentlichung: 2011

Seiten: 30-

Zeitschrift: Proteome Science

Bandnummer: 9

ISSN: 1477-5956

eISSN: 1477-5956

DOI Link: https://doi.org/10.1186/1477-5956-9-30

Verlag: BioMed Central

Abstract: 
Background: Mass spectrometry-based proteomics has reached a stage where it is possible to comprehensively analyze the whole proteome of a cell in one experiment. Here, the employment of stable isotopes has become a standard technique to yield relative abundance values of proteins. In recent times, more and more experiments are conducted that depict not only a static image of the up-or down-regulated proteins at a distinct time point but instead compare developmental stages of an organism or varying experimental conditions.Results: Although the scientific questions behind these experiments are of course manifold, there are, nevertheless, two questions that commonly arise: 1) which proteins are differentially regulated regarding the selected experimental conditions, and 2) are there groups of proteins that show similar abundance ratios, indicating that they have a similar turnover? We give advice on how these two questions can be answered and comprehensively compare a variety of commonly applied computational methods and their outcomes.Conclusions: This work provides guidance through the jungle of computational methods to analyze mass spectrometry-based isotope-labeled datasets and recommends an effective and easy-to-use evaluation strategy. We demonstrate our approach with three recently published datasets on Bacillus subtilis [1,2] and Corynebacterium glutamicum [3]. Special focus is placed on the application and validation of cluster analysis methods. All applied methods were implemented within the rich internet application QuPE [4].

Harvard-Zitierstil: Albaum, S., Hahne, H., Otto, A., Haussmann, U., Becher, D., Poetsch, A., et al. (2011) A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study, Proteome Science, 9, p. 30. https://doi.org/10.1186/1477-5956-9-30

APA-Zitierstil: Albaum, S., Hahne, H., Otto, A., Haussmann, U., Becher, D., Poetsch, A., Goesmann, A., & Nattkemper, T. (2011). A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study. Proteome Science. 9, 30. https://doi.org/10.1186/1477-5956-9-30