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Anal Chem. 2005 Feb 15;77(4):964-73.

PepNovo: de novo peptide sequencing via probabilistic network modeling.

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Department of Computer Science & Engineering, University of California, San Diego, La Jolla, California 92093-0114, USA.


We present a novel scoring method for de novo interpretation of peptides from tandem mass spectrometry data. Our scoring method uses a probabilistic network whose structure reflects the chemical and physical rules that govern the peptide fragmentation. We use a likelihood ratio hypothesis test to determine whether the peaks observed in the mass spectrum are more likely to have been produced under our fragmentation model than under a model that treats peaks as random events. We tested our de novo algorithm PepNovo on ion trap data and achieved results that are superior to popular de novo peptide sequencing algorithms. PepNovo can be accessed via the URL

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