The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
PepNovo: De Novo Peptide Sequencing via Probabilistic Network Modeling
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.
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Cites
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Cited by
Protein Analysis by Shotgun/Bottom-up Proteomics
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InsPecT: Identification of Posttranslationally Modified Peptides from Tandem Mass Spectra
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Self-citationProLuCID: An improved SEQUEST-like algorithm with enhanced sensitivity and specificity
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Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
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JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy
Wang, X., Li, Y., Wu, Z., Wang, H., Tan, H., & Peng, J. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o114.039586 · Cited by 194
Metadata
- Authors
- Frank, A., & Pevzner, P.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2005-01-13
- Volume
- 77
- Issue
- 4
- Pages
- 964-973
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2038615001
- Cited by
- 688
- References
- 16
- FWCI
- 18.51
- Type
- journal article
- Language
- en
- Open access
- closed
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