@article {DBLP:journals/bioinformatics/QuandtHMHMPAL08,
	title = {swissPIT: a novel approach for pipelined analysis of mass spectrometry data},
	journal = {Bioinformatics},
	volume = {24},
	number = {11},
	year = {2008},
	pages = {1416-1417},
	abstract = {The identification and characterization of peptides from tandem mass spectrometry (MS/MS) data represents a critical aspect of proteomics. Today, tandem MS analysis is often performed by only using a single identification program achieving identification rates between 10-50\% (Elias and Gygi, 2007). Beside the development of new analysis tools, recent publications describe also the pipelining of different search programs to increase the identification rate (Hartler et al., 2007; Keller et al., 2005). The Swiss Protein Identification Toolbox (swissPIT) follows this approach, but goes a step further by providing the user an expandable multi-tool platform capable of executing workflows to analyze tandem MS-based data. One of the major problems in proteomics is the absent of standardized workflows to analyze the produced data. This includes the pre-processing part as well as the final identification of peptides and proteins. The main idea of swissPIT is not only the usage of different identification tool in parallel, but also the meaningful concatenation of different identification strategies at the same time. The swissPIT is open source software but we also provide a user-friendly web platform, which demonstrates the capabilities of our software and which is available at http://swisspit.cscs.ch upon request for account.},
	keywords = {bioinformatics, scientific workflow management},
	doi = {10.1093/bioinformatics/btn139},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/18436540},
	author = {Andreas Quandt and Patricia Hernandez and Alexandre Masselot and C{\'e}line Hernandez and Sergio Maffioletti and Cesare Pautasso and Ron D. Appel and Fr{\'e}d{\'e}rique Lisacek}
}
@conference {jophealthgrid07,
	title = {Grid-based Analysis of Tandem Mass Spectrometry Data in Clinical Proteomics},
	booktitle = {Health Grid 2007},
	year = {2007},
	address = {Geneva, Switzerland},
	abstract = {Biomarker detection is one of the greatest challenges in Clinical Proteomics. Today, great hopes are placed into tandem mass spectrometry (MS/MS) to discover potential biomarkers. MS/MS is a technique that allows large scale data analysis, including the identification, characterization, and quantification of molecules. Especially the identification process, that implies to compare experimental spectra with theoretical amino acid sequences stored in specialized databases, has been subject for extensive research in bioinformatics since many years. Dozens of identification programs have been developed addressing different aspects of the identification process but in general, clinicians are only using a single tools for their data analysis along with a single set of specific parameters. Hence, a significant proportion of the experimental spectra do not lead to a confident identification score due to inappropriate parameters or scoring schemes of the applied analysis software. The swissPIT (Swiss Protein Identification Toolbox) project was initiated to provide the scientific community with an expandable multi-tool platform for automated and in-depth analysis of mass spectrometry data. The swissPIT uses multiple identification tools to automatic analyze mass spectra. The tools are concatenated as analysis workflows. In order to realize these calculation-intensive workflows we are using the Swiss Bio Grid infrastructure. A first version of the web-based front-end is available (http://www.swisspit.cscs.ch) and can be freely accessed after requesting an account. The source code of the project will be also made available in near future.},
	keywords = {grid computing, JOpera, scientific workflow management},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/17476043},
	author = {Andreas Quandt and Patricia Hernandez and Peter Kunzst and Cesare Pautasso and Marc Tuloup and Ron D. Appel}
}
