Toward improved peptide feature detection in quantitative proteomics using stable isotope labeling

Reliable detection of peptides in LC‐MS data is a key algorithmic step in the analysis of quantitative proteomics experiments. While highly abundant peptides can be detected reliably by most modern software tools, there is much less agreement on medium and low‐intensity peptides in a sample. The cho...

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Veröffentlicht in:Proteomics. Clinical applications Jg. 9; H. 7-8; S. 706 - 714
Hauptverfasser: Nilse, Lars, Sigloch, Florian Christoph, Biniossek, Martin L., Schilling, Oliver
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Germany Blackwell Publishing Ltd 01.08.2015
Wiley Subscription Services, Inc
Schlagworte:
Animals
Bioinformatics data processing
Chromatography, Liquid
Feature finding
Isotope Labeling - methods
Mass Spectrometry
Mice
Peptides
Peptides - metabolism
Proteins
Proteome - metabolism
Proteomics
Proteomics - methods
Quantitative proteomics
Skin - metabolism
Technology
Bioinformatics data processing
Quantitative proteomics
Technology
Feature finding
ISSN:1862-8346, 1862-8354
Online-Zugang:Volltext
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Zusammenfassung:Reliable detection of peptides in LC‐MS data is a key algorithmic step in the analysis of quantitative proteomics experiments. While highly abundant peptides can be detected reliably by most modern software tools, there is much less agreement on medium and low‐intensity peptides in a sample. The choice of software tools can have a big impact on the quantification of proteins, especially for proteins that appear in lower concentrations. However, in many experiments, it is precisely this region of less abundant but substantially regulated proteins that holds the biggest potential for discoveries. This is particularly true for discovery proteomics in the pharmacological sector with a specific interest in key regulatory proteins. In this viewpoint article, we discuss how the development of novel software algorithms allows us to study this region of the proteome with increased confidence. Reliable results are one of many aspects to be considered when deciding on a bioinformatics software platform. Deployment into existing IT infrastructures, compatibility with other software packages, scalability, automation, flexibility, and support need to be considered and are briefly addressed in this viewpoint article.
Bibliographie:istex:13CEB29658BAAB32B31C977353C3798B7CEF837C
ark:/67375/WNG-JKJF4NNW-J
ArticleID:PRCA1676
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1862-8346
1862-8354
DOI:10.1002/prca.201400173