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swissPIT - Extracting knowledge from mass spectrometry data

English title swissPIT - Extracting knowledge from mass spectrometry data
Applicant Appel Ron David
Number 113456
Funding scheme Project funding
Research institution Institut Suisse de Bioinformatique Centre Médical Universitaire Université de Genève
Institution of higher education Swiss Institute of Bioinformatics - SIB
Main discipline Biochemistry
Start/End 01.10.2006 - 30.09.2009
Approved amount 343'012.00
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Keywords (4)

proteomics; mass spectrometry; identification; characterization

Lay Summary (English)

Lead
Lay summary
Proteomics is is the study of the proteome, the set of proteins produced by a species. Proteomics studies how proteins are expressed and modified, how there are differentially expressed according to varying conditions such as diseases or different drug concentrations.
While each species has only one genome (the set of genes), they have many thousands proteomes, as the proteome varies depending on cellular localisation, time, external influences, etc. Recent technological developments in protein separation techniques and mass spectrometry have made proteomics into one of the key fields of research in life sciences during the last decade. Typically, proteomics involves the separation of proteins contained in biological samples, followed by their analysis by mass spectrometry (MS). The resulting data are fed to specific programs that search their corresponding sequences in protein sequence databases for identification and quantification. Proteomics experiments typically produce up to thousands of MS spectra per day.
While several existing identification programs are routinely used, this part of the process still represents a major bottleneck in proteomics research. Several aspects of protein identification are handled manually and results must be visually validated. More importantly, many (and oftenmost) of the MS data d onot lead to any results at all for multiple causes.
The aims of the swissPIT project are threefold. First it intends to automate the identification process so as to reduce data analysis time, which usually takes longer than data production. Second, it seeks to increase the fraction of spectra that may be identified and to improve the quality and confidence in the identification results by combining several identification algorithms and programs in an automated platform. Third, the platform will be used to carry out a detailed study on the effects and relative importance of the various parameters and algorithms on the identification of proteins, and thus propose optimized identification strategies.
The swissPIT platform will comprise several identification programs developed either in-house or by other international laboratories. Spectra will be successively submitted to several programs The various analysis steps will be uncoupled so as to optimally combine the various strategies and the identification results will be merged using a meta-score. The platform with its many components will be used both for live research by the scientific community and as a benchmarking tool for identification strategies. swissPIT will be linked to the SwissBioGrid intitiative (a GRID for the life sciences) as to benefit from its distributed computing architecture and speed up the analysis time.
The project is expected to solve one the major bottlenecks of current proteomics research by allowing the identification of a larger number of proteins with more confidence and give the community an enhanced automated proteome informatics platform that shall be accessible through the SwissBioGrid.
Direct link to Lay Summary Last update: 21.02.2013

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