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A model of random sequences for de novo peptide sequencing

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4 Author(s)
Jarman, K.D. ; Pacific Northwest Nat. Lab., Richland, WA, USA ; Cannon, W.R. ; Jarman, K.H. ; Heredia-Langner, A.

We present a model for the probability of random sequences appearing in product ion spectra obtained from tandem mass spectrometry experiments using collision-induced dissociation. We demonstrate the use of these probabilities for ranking candidate peptide sequences obtained using a de novo algorithm. Sequence candidates are obtained from a spectrum graph that is greatly reduced in size from those in previous graph-theoretical de novo approaches. Evidence of multiple instances of subsequences of each candidate, due to different fragment ion type series as well as isotopic peaks, is incorporated in a hierarchical scoring scheme. This approach is shown to be useful for confirming results from database search and as a first step towards a statistically rigorous de novo algorithm.

Published in:

Bioinformatics and Bioengineering, 2003. Proceedings. Third IEEE Symposium on

Date of Conference:

10-12 March 2003

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