Name
Title | ||
|---|---|---|
Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass Spectra. |
Abstract | ||
|---|---|---|
Shotgun proteomics is a high-throughput technology used to identify unknown proteins in a complex mixture. At the heart of this process is a prediction task, the spectrum identification problem, in which each fragmentation spectrum produced by a shotgun proteomics experiment must be mapped to the peptide (protein subsequence) which generated the spectrum. We propose a new algorithm for spectrum identification, based on dynamic Bayesian networks, which significantly out-performs the de-facto standard tools for this task: SEQUEST and Mascot. |
Year | Venue | Keywords |
|---|---|---|
2012 | uncertainty in artificial intelligence | biomedical research,bioinformatics |
DocType | Volume | ISSN |
Journal | abs/1210.4904 | 1525-3384 |
Citations | PageRank | References |
2 | 0.44 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ajit P. Singh | 1 | 1072 | 57.74 |
| John Halloran | 2 | 11 | 3.50 |
| Jeff Bilmes | 3 | 3420 | 289.94 |
| Katrin Kirchhoff | 4 | 1026 | 95.24 |
| William Stafford Noble | 5 | 2907 | 203.56 |