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.
Revised: November 10, 2005 |
Published: April 15, 2003
Citation
Jarman K.D., W.R. Cannon, K.H. Jarman, and A. Heredia-Langner. 2003.A model of random sequences for de novo peptide sequencing. In Proceedings of the 3rd IEEE International Symposium on Bioinformatics and Bioengineering, 206-213. Los Alamitos, California:IEEE Computer Society.PNNL-SA-39306.