Using statistical models to identify factors that have a role in defining the abundance of ions produced by tandem MS

Analytical Chemistry

Volumn 79, Issue 15, 2007, Pages 5601-5607

  Barton, Sheila J ^a   Richardson, Sylvia ^b   Perkins, David N ^c   Bellahn, Inga ^b   Bryant, Trevor N ^a   Whittaker, John C ^d  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c UNIVERSITY OF LEEDS   (United Kingdom)

^d LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; MASS SPECTROMETRY; MATHEMATICAL MODELS; PHYSICAL CHEMISTRY; STATISTICAL METHODS;

FRAGMENTING PEPTIDES; MASCOT ALGORITHMS; PROTEINS DIGESTION; STATISTICAL MODELS;

PEPTIDES;

AMINO ACID; ION; PEPTIDE; TRYPSIN;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; DATA BASE; MASS; PEPTIDE ANALYSIS; PHYSICAL CHEMISTRY; PROTEIN DEGRADATION; QUADRUPOLE MASS SPECTROMETRY; STATISTICAL MODEL; TANDEM MASS SPECTROMETRY;

ALGORITHMS; AMINO ACIDS; DATA INTERPRETATION, STATISTICAL; DATABASES, PROTEIN; IONS; MODELS, STATISTICAL; PEPTIDES; PROBABILITY; TANDEM MASS SPECTROMETRY; TRYPSIN;

EID: 34547732831     PISSN: 00032700     EISSN: None     Source Type: Journal    
DOI: 10.1021/ac0700272     Document Type: Article

References (28)

1. Proteomics. American Medical Association. http://www.ama-assn.org/ama/ pub/category/print/3668.html (accessed December 10, 2004).
2. Aebersold, R.; Goodlett, D. R. Chem. Rev. 2001, 101, 269-295.
3. Aebersold, R.; Mann, M. Nature 2003, 422, 198-207.
4. Perkins, D. N.; Pappin, D. J.; Creasy, D. M.; Cottrell, J. S. Electrophoresis 1999, 20, 3551-3567.
5. Yates, J. R., III; Eng, J. K.; McCormack, A. L.; Schieltz, D. Anal. Chem. 1995, 67, 1426-1436.
6. Polce, M. J.; Ren, D.; Wesdemiotis, C. J. Mass Spectrom. 2000, 35, 1391-1398.
7. Biemann, K. Biomed. Environ. Mass Spectrom. 1988, 16, 99-111.
8. Roepstorff, P.; Fohlman, J. Biomed. Mass Spectrom. 1984, 11, 601.
9. Wysocki, V. H.; Tsaprailis, G.; Smith, L. L.; Bred, L. A. J. Mass Spectrom. 2000, 35, 1399-1406.
10. Fenyo, D.; Qin, J.; Chait, B. T. Electrophoresis 1998, 19, 998-1005.
11. Huang, Y.; Triscari, J. M.; Pasa-Tolic, L.; Anderson, G. A.; Lipton, M. S.; Smith, R. D.; Wysocki, V. H. J. Am. Chem. Soc. 2004, 126, 3034-3035.
12. Huang, Y.; Triscari, J. M.; Tseng, G. C.; Pasa-Tolic, L.; Lipton, M. S.; Smith, R. D.; Wysocki, V. H. Anal. Chem. 2005, 77, 5800-5813.
13. Kapp, E. A.; Schutz, F.; Reid, G. E.; Eddes, J. S.; Moritz, R. L.; O'Hair, R. A.; Speed, T. P.; Simpson, R. J. Anal. Chem. 2003, 75, 6251-6264.
14. Schutz, F.; Kapp, E. A.; Simpson, R. J.; Speed, T. P. Biochem. Soc. Trans. 2003, 31, 1479-1483.
15. Tabb, D. L.; Smith, L. L.; Breci, L. A.; Wysocki, V. H.; Lin, D.; Yates, J. R., III. Anal. Chem. 2003, 75, 1155-1163.
16. Paizs, B.; Suhai, S. Mass Spectrom. Rev. 2005, 24, 508-548.
17. Taylor, J. A.; Johnson, R. S. Anal. Chem. 2001, 73, 2594-2604.
18. Zhu, W.; Wang, X.; Ma, Y.; Rao, M.; Glimm, J.; Kovach, J. S. Proc. Natl. Acad. Sci. U.S.A 2003, 100, 14666-14671.
19. Box, G. E. P.; Cox, D. R. J. R. Stat. Soc., B 1964, 26, 211-252.
20. Hastie, T. J.; Tibshirani, R. J.; Friedman, J. The Elements of Statistical Learning: Data Mining, Inference and Prediction; Springer-Verlag, Inc.: New York, 2001; Chapter 5.
21. Zamyatin, A. A. Prog. Biophys. Mol. Biol. 1972, 24, 107-123.
22. Chotia, C. J. Mol. Biol. 1975, 105, 1-14.
23. Eisenberg, D. Annu. Rev. Biochem. 1984, 53, 595-623.
24. Kyte, J.; Doolittle, R. F. J. Mol. Biol. 1982, 157, 105-132.
25. Bienvenut, W. V.; Hoogland, C.; Greco, A.; Heller, M.; Gasteiger, E.; Appel, R. D.; Diaz, J. J.; Sanchez, J. C.; Hochstrasser, D. F. Rapid Commun. Mass Spectrom. 2002, 16, 616-626.
26. Gorman, G. S.; Speir, J. P.; Turner, C. A.; Amster, I. J. J. Am. Chem. Soc. 1992, 114, 3986-3988.
27. Wysocki, V. H.; Resing, K. A.; Zhang, Q. F.; Cheng, G. L. Methods 2005, 35, 211-222.
28. Akaike, H. IEEE Trans. Autom. Control 1974, AC19, 716-723.