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Activity Number: 154
Type: Contributed
Date/Time: Monday, July 30, 2007 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #310386
Title: Statistical Methods for Peptide Identification Using Tandem Mass Spectrometry Through Sequence Database Searching
Author(s): Qunhua Li*+ and Matthew Stephens
Companies: University of Washington and The University of Chicago
Address: 4747 30th Ave NE 155, Seattle, WA, 98105,
Keywords: mixture models ; EM algorithm ; mass spectrometry ; proteomics ; peptide identification

Peptide identification using tandem mass spectra through database searching is a key component in proteomic research. In this study, we developed a model-based scoring algorithm for peptide identification using mixture models. It effectively takes account of the spectral noise and incorporates the spectral intensity. In addition, our approach also provides a natural confidence measure for assessing the uncertainty of the score. We will present our results on several public available benchmark datasets.

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Revised September, 2007