Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/BIBE.2003.1188948 | BIBE |
Keywords | DocType | ISBN |
molecular biophysics,organic compounds,physiological models,probability,de novo peptide sequencing,fragment ion type series,hierarchical scoring scheme,isotopic peaks,random sequences appearance probability,random sequences model,statistically rigorous de novo algorithm,subsequences | Conference | 0-7695-1907-5 |
Citations | PageRank | References |
4 | 0.66 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kenneth D Jarman | 1 | 18 | 4.05 |
| William R. Cannon | 2 | 69 | 10.68 |
| Kristin H. Jarman | 3 | 18 | 2.41 |
| Alejandro Heredia-langner | 4 | 20 | 4.04 |