Name
Abstract | ||
|---|---|---|
Peptide sequencing from mass spectrometry data is a key step in proteome research. Especially de novo sequencing, the identification of a peptide from its spectrum alone, is still a challenge even for state-of-the-art algorithmic approaches. In this paper, we present ANTILOPE, a new fast and flexible approach based on mathematical programming. It builds on the spectrum graph model and works with a variety of scoring schemes. ANTILOPE combines Lagrangian relaxation for solving an integer linear programming formulation with an adaptation of Yen’s k shortest paths algorithm. It shows a significant improvement in running time compared to mixed integer optimization and performs at the same speed like other state-of-the-art tools. We also implemented a generic probabilistic scoring scheme that can be trained automatically for a data set of annotated spectra and is independent of the mass spectrometer type. Evaluations on benchmark data show that ANTILOPE is competitive to the popular state-of-the-art programs PepNovo and NovoHMM both in terms of runtime and accuracy. Furthermore, it offers increased flexibility in the number of considered ion types. ANTILOPE will be freely available as part of the open source proteomics library OpenMS. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TCBB.2011.59 | IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM |
Keywords | Field | DocType |
biology computing,linear programming,mass spectroscopy,molecular biophysics,proteins,proteomics,lagrangian relaxation approach,novohmm,openms,pepnovo,antilope,de novo peptide sequencing,integer linear programming,mass spectrometry,open source proteomics library,proteome research,scoring schemes,spectrum graph model,computational proteomics,lagrangian relaxation,discrete optimization.,algorithm design and analysis,mass spectrometer,shortest path algorithm,mathematical programming,databases,amino acids,discrete optimization,biological sciences,computational biology,optimization,spectrum | Integer,Algorithm design,Computer science,Discrete optimization,De novo peptide sequencing,Integer programming,Linear programming,Lagrangian relaxation,Bioinformatics,Probabilistic logic | Journal |
Volume | Issue | ISSN |
9 | 2 | 1545-5963 |
Citations | PageRank | References |
5 | 0.46 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandro Andreotti | 1 | 9 | 1.93 |
| Gunnar W. Klau | 2 | 869 | 55.67 |
| Knut Reinert | 3 | 1020 | 105.87 |