Computational Tools for High Throughput Quantitative Proteomic Analysis


Over the past few years, a number of promising tandem mass spectrometry
based methods have been developed for large-scale quantitative protein
profiling. As in case of gene expression microarray studies, the major bottleneck
of large-scale proteomics experiments lies in the processing, management, and
interpretation of the vast amount of acquired experimental data.  In order to
facilitate the global analysis of quantitative proteomics studies using mass
spectrometry, we developed a set of computational tools that range from the
identification of peptides via sequence database searching, the validation of
 peptide and protein identifications using robust statistical models, the
 organization of the data in a relational database to the interpretation of
 proteomic data in the context of functional modules and biological pathways.
The suite of software tools will be available to all freely and as open source.
 

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Alexey Nesvizhskii       nesvi@systemsbiology.org
Institute for Systems Biology