Poster: De novo protein identification by dynamic programming

In this paper we present a new de novo method to identify protein and peptide amino acid sequences from tandem mass spectrometry (MS/MS) data. Our approach uses an integer knapsack dynamic programming formulation, which allows for optimization to directly consider ions other than the typical b and y variety. Rather than acting as “noise” which obscures the sequence in question, the additional ions can be used to improve identifications, and provide greater confidence in the results. We validate our approach using raw experimental data.