MS-Dictionary

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Contact: Sangtae Kim [sak008 (at) ucsd.edu]

Summary

Database search tools identify peptides by matching tandem mass spectra against a protein database. We study an alternative approach when all plausible de novo interpretations of a spectrum (spectral dictionary) are generated and then quickly matched against the database. We present a new MS-Dictionary algorithm for efficiently generating spectral dictionaries and demonstrate that MS-Dictionary can identify spectra that are missed in the database search. We argue that MS-Dictionary enables proteogenomic searches in six-frame translation of genomic sequences that may be prohibitively time-consuming for existing database search approaches. We show that such searches allow one to correct sequencing errors and find programmed frameshifts.


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Publications

Spectral Dictionaries: Integrating De Novo Peptide Sequencing with Database Search of Tandem Mass Spectra.
Sangtae Kim, Nitin Gupta and Pavel Pevzner.
Submitted.

 

Latest Releases

PepNovo

2008.07.08

MS-Clustering

2008.06.09

Inspect, MS-Alignment

2008.04.04

MS-Dictionary

2007.11.30

MS-GeneratingFunction

2007.11.28

Spectral Networks

Sept 2007

 

 

 

Media Coverage


A powerful tool for PTM discovery (Jan 2008, Journal of Proteome research, Vol 7. Issue 1)


From spectral networks to shotgun sequencing (June 2007, Nature Methods, Vol. 4 No. 6)

Identifying peptides without a database (May 2007, Journal of Proteome Research)

UCSD Computer Scientist Wins Young Investigator Award, Research on Snake Venom Proteins Highlighted (Nov 2006, UCSD)