@Article{Albaum:Neuweger:Franzel:Qupe_Rich_Inter:2009,
  author =	 {S. P. Albaum and H. Neuweger and B. Franzel and S. Lange 
                  and D. Mertens and C. Trotschel and D. Wolters and J. 
                  Kalinowski and T. W. Nattkemper and A. Goesmann},
  title =	 {Qupe--a {Rich} {Internet} {Application} to take a step 
                  forward in the analysis of mass spectrometry-based 
                  quantitative proteomics experiments},
  journal =	 {Bioinformatics},
  year =	 {2009},
  volume =	 {25},
  number =	 {23},
  pages =	 {3128-3134},
  user =	 {sita},
  pmid =	 {19808875},
  doi = 	 {10.1093/bioinformatics/btp568},
  abstract =	 {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. 
                  Availability and Implementation: Qupe is implemented in Java 
                  utilizing Hibernate, Echo2, R and the Spring framework. We 
                  encourage the usage of the RIA in the sense of the 'software 
                  as a service' concept, maintained on our servers and 
                  accessible at the following location: 
                  http://qupe.cebitec.uni-bielefeld.de CONTACT: 
                  stefan.albaum@cebitec.uni-bielefeld.de SUPPLEMENTARY 
                  INFORMATION: Supplementary data are available at 
                  Bioinformatics online.}
}