Computationally Intensive Research Project
Bioinformatics Tools to Define the Proteomic State of the Cell
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William R. Cannon1, Gordon A. Anderson2, Christopher Stephen Oehmen1, Kristin H Jarman1, Douglas J Baxter2, Joel Marcel Malad1, Alejandro Heredia-Langner1
1Pacific Northwest National Laboratory, 2Environmental Molecular Sciences Laboratory
FY07 Allocation - 100,000
Abstract
During the next three years we will enhance mass spectrometry-based proteomic analysis by building a new generation of tools for peptide identification. The accurate identification of protein complexes in the majority of mass spectrometry-based techniques relies on accurate identification of peptides by tandem mass spectrometry (MS/MS). Currently, approximately 90-85% of MS/MS spectra cannot be identified with a peptide for a number of reasons. In this project, we will develop statistical models that will more accurately describe the various aspects of the identification process. This will include statistical mechanical models in the case of peptide fragmentation and sophisticated conditional probability networks in the case of using the fragmentation patterns in scoring spectra. We will develop computational, evolutionary methods specifically suited for solving the combinatorial problem of identifying post-translational modifications to peptides. The result of the development will be to increase the number of identified peptides from the current level of approximately 10% to a level exceeding 25%.
