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.
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)