Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments
Albaum S, Neuweger H, Fraenzel B, Lange S, Mertens D, Troetschel C, Wolters D, Kalinowski J, Nattkemper TW, Goesmann A (2009)
Bioinformatics 25(23): 3128-3134.
Zeitschriftenaufsatz
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Autor*in
Albaum, StefanUniBi ;
Neuweger, HeikoUniBi;
Fraenzel, Benjamin;
Lange, Sita;
Mertens, Dominik;
Troetschel, Christian;
Wolters, Dirk;
Kalinowski, JörnUniBi;
Nattkemper, Tim WilhelmUniBi ;
Goesmann, AlexanderUniBi
Einrichtung
Technische Fakultät > AG Genominformatik
Centrum für Biotechnologie > Arbeitsgruppe J. Kalinowski
Centrum für Biotechnologie > Arbeitsgruppe A. Goesmann
Centrum für Biotechnologie > Technologieplattformen > Bioinformatics Resource Facility
Technische Fakultät > AG Biodata Mining
Center of Excellence - Cognitive Interaction Technology CITEC
Centrum für Biotechnologie > Arbeitsgruppe T. Nattkemper
Centrum für Biotechnologie > Institut für Bioinformatik
Centrum für Biotechnologie > Institut für Genomforschung und Systembiologie
Technische Fakultät > Computational Genomics
Centrum für Biotechnologie > Arbeitsgruppe J. Kalinowski
Centrum für Biotechnologie > Arbeitsgruppe A. Goesmann
Centrum für Biotechnologie > Technologieplattformen > Bioinformatics Resource Facility
Technische Fakultät > AG Biodata Mining
Center of Excellence - Cognitive Interaction Technology CITEC
Centrum für Biotechnologie > Arbeitsgruppe T. Nattkemper
Centrum für Biotechnologie > Institut für Bioinformatik
Centrum für Biotechnologie > Institut für Genomforschung und Systembiologie
Technische Fakultät > Computational Genomics
Abstract / Bemerkung
Motivation: The goal of present-omics sciences is to understand biological systems as a whole in terms of interactions of the individual cellular components. One of the main building blocks in this field of study is proteomics where tandem mass spectrometry (LC-MS/MS) in combination with isotopic labelling techniques provides a common way to obtain a direct insight into regulation at the protein level. Methods to identify and quantify the peptides contained in a sample are well established, and their output usually results in lists of identified proteins and calculated relative abundance values. The next step is to move ahead from these abstract lists and apply statistical inference methods to compare measurements, to identify genes that are significantly up-or down-regulated, or to detect clusters of proteins with similar expression profiles. Results: We introduce the Rich Internet Application (RIA) Qupe providing comprehensive data management and analysis functions for LC-MS/MS experiments. Starting with the import of mass spectra data the system guides the experimenter through the process of protein identification by database search, the calculation of protein abundance ratios, and in particular, the statistical evaluation of the quantification results including multivariate analysis methods such as analysis of variance or hierarchical cluster analysis. While a data model to store these results has been developed, a well-defined programming interface facilitates the integration of novel approaches. A compute cluster is utilized to distribute computationally intensive calculations, and a web service allows to interchange information with other -omics software applications. To demonstrate that Qupe represents a step forward in quantitative proteomics analysis an application study on Corynebacterium glutamicum has been carried out.
Erscheinungsjahr
2009
Zeitschriftentitel
Bioinformatics
Band
25
Ausgabe
23
Seite(n)
3128-3134
ISSN
1367-4803
eISSN
1460-2059
Page URI
https://pub.uni-bielefeld.de/record/1589531
Zitieren
Albaum S, Neuweger H, Fraenzel B, et al. Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments. Bioinformatics. 2009;25(23):3128-3134.
Albaum, S., Neuweger, H., Fraenzel, B., Lange, S., Mertens, D., Troetschel, C., Wolters, D., et al. (2009). Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments. Bioinformatics, 25(23), 3128-3134. https://doi.org/10.1093/bioinformatics/btp568
Albaum, Stefan, Neuweger, Heiko, Fraenzel, Benjamin, Lange, Sita, Mertens, Dominik, Troetschel, Christian, Wolters, Dirk, Kalinowski, Jörn, Nattkemper, Tim Wilhelm, and Goesmann, Alexander. 2009. “Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments”. Bioinformatics 25 (23): 3128-3134.
Albaum, S., Neuweger, H., Fraenzel, B., Lange, S., Mertens, D., Troetschel, C., Wolters, D., Kalinowski, J., Nattkemper, T. W., and Goesmann, A. (2009). Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments. Bioinformatics 25, 3128-3134.
Albaum, S., et al., 2009. Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments. Bioinformatics, 25(23), p 3128-3134.
S. Albaum, et al., “Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments”, Bioinformatics, vol. 25, 2009, pp. 3128-3134.
Albaum, S., Neuweger, H., Fraenzel, B., Lange, S., Mertens, D., Troetschel, C., Wolters, D., Kalinowski, J., Nattkemper, T.W., Goesmann, A.: Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments. Bioinformatics. 25, 3128-3134 (2009).
Albaum, Stefan, Neuweger, Heiko, Fraenzel, Benjamin, Lange, Sita, Mertens, Dominik, Troetschel, Christian, Wolters, Dirk, Kalinowski, Jörn, Nattkemper, Tim Wilhelm, and Goesmann, Alexander. “Qupe-a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments”. Bioinformatics 25.23 (2009): 3128-3134.
Daten bereitgestellt von European Bioinformatics Institute (EBI)
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An easy-to-use Decoy Database Builder software tool, implementing different decoy strategies for false discovery rate calculation in automated MS/MS protein identifications.
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DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics.
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The COG database: an updated version includes eukaryotes.
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Zhang N, Aebersold R, Schwikowski B., Proteomics 2(10), 2002
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Zhu H, Pan S, Gu S, Bradbury EM, Chen X., Rapid Commun. Mass Spectrom. 16(22), 2002
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Zhu H, Pan S, Gu S, Bradbury EM, Chen X., Rapid Commun. Mass Spectrom. 16(22), 2002
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