De novo peptide sequencing and spectral alignment algorithm via tandem mass spectrometry
thesis · 2012
| Date | 2012-01-01 |
| Type | thesis |
| Publisher | PhD thesis |
| Contribution | algorithm |
| DOI | 10.25549/usctheses-m2651 |
| Citations (OpenAlex) | 0 |
Abstract
Tandem mass spectrometry (MS/MS) has become an important experimental method for high throughput proteomics based biological discovery. The most common usage of MS/MS in biological applications is peptide sequencing. In this thesis, we focus on algorithms for MS/MS peptide identification and spectral alignment. We carry out two studies: (1) We have developed a de novo sequencing algorithm called MSNovo that integrates a new probabilistic scoring function with a mass array based dynamic programming algorithm. MSNovo works on various MS data generated from both LCQ and LTQ mass spectrometers and interprets singly, doubly and triply charged ions. MSNovo was tested to perform better than previous algorithms on several datasets. (2)We have developed a spectrum-peptide and spectrum-spectrum alignment algorithms called MSPEP. MSPEP identifies Post Translational Modifications through the spectrum-peptide alignment algorithm and reveals the relationship among unknown peptides through thespectrum-spectrum alignment algorithm.
Methods and tools
- MSNovo: Mass-array dynamic programming