Spectrum Identification using a Dynamic Bayesian Network Model of Tandem   Mass Spectra
  Shotgun proteomics is a high-throughput technology used to identify unknown proteins in a complex mixture. At the heart of this process is a prediction task, the spectrum identification problem, in which each fragmentation spectrum produced by a shotgun proteomics experiment must be mapped to the peptide (protein subsequence) which generated the spectrum. We propose a new algorithm for spectrum identification, based on dynamic Bayesian networks, which significantly outperforms the de-facto standard tools for this task: SEQUEST and Mascot. 
Ajit P. Singh, John Halloran, Jeff A. Bilmes, Katrin Kirchoff, William   S. Noble
cs.CE q-bio.QM