Tandem mass intensity estimation for de novo peptide sequencing
peer-reviewed · 2018 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) · 2018
| Date | 2018-05-01 |
| Type | peer-reviewed |
| Venue | 2018 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) |
| Publisher | IEEE |
| Contribution | algorithm |
| DOI | 10.1109/cibcb.2018.8404971 |
| Citations (OpenAlex) | 0 |
Abstract
Many de novo approaches have been developed for peptide identification. Most of these methods attempt to build a decision function starting from similarity measures associated to theoretical spectra of candidate peptides to identify the most similar one to a given experimental spectrum. In this paper, we propose a de novo peptide sequencing method that takes into account the peak intensity distribution in order to apply it in a probabilistic scoring model to rank candidate peptide matches. The purpose of our approach is to highlight the relationship between peak intensities and peptide cleavage positions on the one hand and to show its impact on de novo peptide identification on the other hand. To evaluate our method, a set of experiments have been undertaken into high mass spectrum accuracy data sets. The obtained results show the effectiveness of our approach.
Methods and tools
- Intensity-based probabilistic de novo scoring: De novo sequencing that models the peak intensity distribution in a probabilistic score, relating intensities to cleavage positions to rank candidate peptides.