title: Spectral dictionaries: Integrating de novo peptide sequencing with database search of tandem mass spectra.
abstract: 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 proteogenomics 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.
authors.affiliation: Department of Computer Science and Engineering, University of California San Diego, La Jolla, California 92093, USA.
authors.forename: Sangtae
authors.initials: S
authors.lastname: Kim
authors.forename: Nitin
authors.initials: N
authors.lastname: Gupta
authors.forename: Nuno
authors.initials: N
authors.lastname: Bandeira
authors.forename: Pavel A
authors.initials: PA
authors.lastname: Pevzner
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D030562:Databases, Protein; D015894:Genome, Human; D006801:Humans; D008969:Molecular Sequence Data; D010455:Peptides / Q000032:analysis / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*; D020592:Shewanella / Q000737:chemistry; D053719:Tandem Mass Spectrometry / Q000379:methods*
chemical_list: D010455:Peptides