A Hidden Markov Model for de Novo Peptide Sequencing

Part of Advances in Neural Information Processing Systems 17 (NIPS 2004)

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Bernd Fischer, Volker Roth, Jonas Grossmann, Sacha Baginsky, Wilhelm Gruissem, Franz Roos, Peter Widmayer, Joachim Buhmann


De novo Sequencing of peptides is a challenging task in proteome re- search. While there exist reliable DNA-sequencing methods, the high- throughput de novo sequencing of proteins by mass spectrometry is still an open problem. Current approaches suffer from a lack in precision to detect mass peaks in the spectrograms. In this paper we present a novel method for de novo peptide sequencing based on a hidden Markov model. Experiments effectively demonstrate that this new method signif- icantly outperforms standard approaches in matching quality.