Grid-based Analysis of Tandem Mass Spectrometry Data in Clinical Proteomics

TitleGrid-based Analysis of Tandem Mass Spectrometry Data in Clinical Proteomics
Publication TypeConference Paper
Year of Publication2007
AuthorsQuandt, A., P. Hernandez, P. Kunzst, C. Pautasso, M. Tuloup, and R. D. Appel
Conference NameHealth Grid 2007
Conference LocationGeneva, Switzerland
Keywordsgrid computing, JOpera, scientific workflow management

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 ( and can be freely accessed after requesting an account. The source code of the project will be also made available in near future.

Citation Keyjophealthgrid07
Refereed DesignationRefereed