APPLICATION OF COMBINATORIAL METHODS TO PROTEIN IDENTIFICATION IN PEPTIDE MASS FINGERPRINTING
Leonid Molokov
2010
Abstract
Peptide Mass Fingerprinting (PMF) for long has been a widely used and reliable method for protein identification. However it faced several problems, the most important of which is inability of classical methods to deal with protein mixtures. To cope with this problem, more costly experimental techniques are employed. We investigate, whether it is possible to extract more information from PMF by more thorough data analysis. To do this, we propose a novel method to remove noise from the data and show how the results can be interpreted in a different way. We also provide simulation results suggesting our method can be used for analysis of small mixtures.
References
- Aebersold, R. and Mann, M. (2003). Mass spectrometrybased proteomics. Nature, 422:198-207.
- Clauser, K., Baker, P., and Burlingame, A. (1999). Role of accurate mass measurement (+/- 10 ppm) in protein identification strategies employing ms or ms/ms and database searching. Anal. Chem., 71(14):2871-2882.
- Damaschke, P. and Molokov, L. (2009). The union of minimal hitting sets : combinatorial parameterized bounds and counting. J. Discrete Algorithms, 7:391-401.
- Fernau, H. (2006). Parameterized algorithms for hitting set: The weighted case. In CIAC'06, volume 41, pages 332-343.
- He, Z., Yang, C., Yang, C., Qi, R. Z., Tam, J., and Yu, W. (2009). Optimization-based peptide mass fingerprinting for protein mixture identification. In RECOMB'09, pages 16-30. LNCS 5541.
- Lund, C. and Yannakakis, M. (1994). On the hardness of approximating minimization problems. Journal of the ACM, 41(5):960-981.
- Nesvizhskii, A. I. and Aebersold, R. (2005). Interpretation of shotgun proteomic data: The protein inference problem. Mol. Cel. Proteomics, 4:1419-1440.
- Perkins, D. N., Pappin, D. J. C., Creasy, D. M., and Cottrell, J. S. (1999). Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis, 20:3551-3567.
- Samuelsson, J., Dalevi, D., Levander, F., and Rognvaldsson, T. (2004). Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting. Bioinformatics, 20(18):3628-3635.
- Zhang, W. and Chait, B. T. (2000). Profound: an expert system for protein identification using mass spectrometric peptide mapping information. Anal. Chem., 72(11):2482-2489.
Paper Citation
in Harvard Style
Molokov L. (2010). APPLICATION OF COMBINATORIAL METHODS TO PROTEIN IDENTIFICATION IN PEPTIDE MASS FINGERPRINTING . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 307-313. DOI: 10.5220/0003102703070313
in Bibtex Style
@conference{kdir10,
author={Leonid Molokov},
title={APPLICATION OF COMBINATORIAL METHODS TO PROTEIN IDENTIFICATION IN PEPTIDE MASS FINGERPRINTING},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={307-313},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003102703070313},
isbn={978-989-8425-28-7},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - APPLICATION OF COMBINATORIAL METHODS TO PROTEIN IDENTIFICATION IN PEPTIDE MASS FINGERPRINTING
SN - 978-989-8425-28-7
AU - Molokov L.
PY - 2010
SP - 307
EP - 313
DO - 10.5220/0003102703070313