DocumentCode
3409411
Title
PPM-chain - de novo peptide identification program comparable in performance to Sequest
Author
Day, Robert M. ; Borziak, Andrey ; Gorin, Andrey
Author_Institution
Oak Ridge Nat. Lab., TN, USA
fYear
2004
fDate
16-19 Aug. 2004
Firstpage
505
Lastpage
508
Abstract
Recently, we introduced probability profile method (PPM), which utilizes neutral-loss neighborhoods around each peak in MS/MS spectrum to "label" it: to assign a probability that the peak in question belongs to one of the specific categories (such as b- or y-ion peaks). Here we present the PPM-chain program - a PPM-based tool for de novo protein tag identification. De novo peptide identification involves finding a connected sequence of ion peaks separated by amino acid mass intervals, corresponding to a tag - partial peptide of the source protein. In the existing approaches the number of the possible connected sequences may run into hundreds of thousands, and it increases exponentially with the desired length of the tag. PPM can be used to locate high probability islands, containing very pure sets of b- and y-ion peaks, thereby reducing computational complexity and sharply increasing precision of tagging. In addition, the obtained tags can be reliably ranked using PPM-derived probabilities assigned to the connected peaks. The value of peptide tags was demonstrated on a large database of ∼20,000 spectra. With the additional flanking mass constraints PPM-chain shows precision and coverage similar to the field industrial-power standard - Sequest program, while providing a set of novel unique capabilities and significantly outperforming Sequest in speed.
Keywords
biology computing; computational complexity; mass spectra; molecular biophysics; probability; proteins; Sequest program; amino acid; computational complexity; de novo peptide identification program; de novo protein tag identification; ion peaks; mass spectroscopy; neutral-loss neighborhoods; probability profile method-chain program; Amino acids; Computational biology; Computational complexity; Computer science; Databases; Laboratories; Mathematics; Peptides; Proteins; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE
Print_ISBN
0-7695-2194-0
Type
conf
DOI
10.1109/CSB.2004.1332477
Filename
1332477
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