PepNovo: de novo peptide sequencing via probabilistic network modeling

peer-reviewed · Analytical Chemistry · 2005

peer-reviewed · Analytical Chemistry · 2005. Ari Frank et al. We present a novel scoring method for de novo interpretation of peptides from tandem mass spectrometry data…
Date 2005-02-15
Type peer-reviewed
Venue Analytical Chemistry
Publisher American Chemical Society (ACS)
Contribution algorithm
DOI 10.1021/ac048788h
Citations (OpenAlex) 691
Venue 2-year citedness 7.10

Abstract

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 http://www-cse.ucsd.edu/groups/bioinformatics/software.html.

Authors

  1. Ari Frank · Affectivon, Inc., Max Planck Institute of Molecular Cell Biology and Genetics, University of California San Diego
  2. Pavel A. Pevzner · Max Planck Institute of Molecular Cell Biology and Genetics, Saint Petersburg Academic University, St Petersburg University, St. Petersburg State University, University of California San Diego, University of Southern California

Methods and tools

  • PepNovo: Probabilistic network + DP

Cites (6)

Cited by (231)

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