Bioinformatics challenges in mass spectrometry-driven proteomics

Methods in Molecular Biology

Volumn 753, Issue , 2011, Pages 359-371

  Martens, Lennart ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

Bioinformatics; Databases; Identification; Mass spectrometry; Quantification

Indexed keywords

PEPTIDE; PROTEIN;

ALGORITHM; ARTICLE; BIOLOGY; CHEMISTRY; COMPUTER PROGRAM; MASS SPECTROMETRY; METHODOLOGY; PROTEIN DATABASE; PROTEOMICS;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; MASS SPECTROMETRY; PEPTIDES; PROTEINS; PROTEOMICS; SOFTWARE;

EID: 80052347088     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-61779-148-2_24     Document Type: Article

References (54)

1. Domon B. and Aebersold R. (2006) Mass spectrometry and protein analysis. Science 312, 212-217.
2. Hubbard T., Aken B., Ayling S., Ballester B., Beal K., Bragin E. et al. (2009) Ensembl 2009. Nucleic Acids Res 37, D690-D697.
3. The UniProt Consortium (2009) The universal protein resource (UniProt) 2009. Nucleic Acids Res 37, D169-D174.
4. Sadygov R.G., Cociorva D. and Yates J.R. (2004) Large-scale database searching using tandem mass spectra: Looking up the answer in the back of the book Nat Methods 1, 195-202.
5. Gevaert K., Van Damme P., Ghesquière B., Impens F., Martens L., Helsens K. et al. (2007) A la carte proteomics with an emphasis on gel-free techniques. Proteomics 7, 2698-2718.
6. Martens L., Nesvizhskii A.I., Hermjakob H., Adamski M., Omenn G.S., Vandekerckhove J. et al. (2005) Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories. Proteomics 5, 3501-3505.
7. Martens L. and Hermjakob H. (2007) Proteomics data validation: Why all must provide data. Mol Biosyst 3, 518-522.
8. Boyne M.T., Garcia B.A., Li M., Zamdborg L., Wenger C.D., Babai S. et al. (2009) Tandem mass spectrometry with ultrahigh mass accuracy clarifies peptide identification by database retrieval. J Proteome Res 8, 374-379.
9. Vaudel M., Sickmann A. and Martens L. (2009) Peptide and protein quantification: A map of the minefield. Proteomics 10, 650-670.
10. Cox J. and Mann M. (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26, 1367-1372.
11. Zhang J., Xu D., Gao W., Lin G. and He S. (2009) Isotope pattern vector based tandem mass spectral data calibration for improved peptide and protein identification. Rapid Commun Mass Spectrom 23, 3448-3456.
12. Zhang X., Asara J.M., Adamec J., Ouzzani M. and Elmagarmid A.K. (2005) Data pre-processing in liquid chromatography-mass spectrometry-based proteomics. Bioinformatics 21, 4054-4059.
13. Kwon D., Vannucci M., Song J.J., Jeong J. and Pfeiffer R.M. (2008) A novel wavelet-based thresholding method for the preprocessing of mass spectrometry data that accounts for heterogeneous noise. Proteomics 8, 3019-3029.
14. Renard B.Y., Kirchner M., Monigatti F., Ivanov A.R., Rappsilber J., Winter D. et al. (2009) When less can yield more - Computational preprocessing of MS/MS spectra for peptide identification. Proteomics 9, 4978-4984.
15. Matthiesen R. (2007) Methods, algorithms and tools in computational proteomics: A practical point of view. Proteomics 7, 2815-2832.
16. Nesvizhskii A.I., Vitek O. and Aebersold R. (2007) Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat Methods 4, 787-797.
17. Perkins D.N., Pappin D.J., Creasy D.M. and Cottrell J.S. (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551-3567.
18. Eng J.K., McCormack A.L. and Yates J.R. (1994) An approach to correlate tandem mass-spectral data of peptides with amino-acid-sequences in a protein database. J Am Soc Mass Spectrom 5, 976-989.
19. Craig R. and Beavis R. (2004) TANDEM: matching proteins with tandem mass spectra. Bioinformatics (Oxford, England) 20, 1466-1467.
20. Geer L.Y., Markey S.P., Kowalak J.A., Wagner L., Xu M., Maynard D.M. et al. (2004) Open mass spectrometry search algorithm. J Proteome Res 3, 958-964.
21. Tabb D.L., Fernando C.G. and Chambers M.C. (2007) MyriMatch: Highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis. J Proteome Res 6, 654-661.
22. Kapp E.A., Schütz F., Connolly L.M., Chakel J.A., Meza J.E., Miller C.A. et al. (2005) An evaluation, comparison, and accurate bench-marking of several publicly available MS/MS search algorithms: Sensitivity and specificity analysis. Proteomics 5, 3475-3490.
23. Keller A., Nesvizhskii A.I., Kolker E. and Aebersold R. (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search Anal Chem 74, 5383-5392.
24. Käll L., Storey J.D. and Noble W.S. (2008) Non-parametric estimation of posterior error probabilities associated with peptides identified by tandem mass spectrometry Bioinformatics 24, 42-48.
25. Helsens K., Timmerman E., Vandekerckhove J., Gevaert K. and Martens L. (2008) Peptizer, a tool for assessing false positive Peptide identifications and manually validating selected results Mol Cell Proteomics 7, 2364-2372.
26. Martens L., Vandekerckhove J. and Gevaert K. (2005) DBToolkit: Processing protein databases for peptide-centric proteomics Bioinformatics 21, 3584-3585.
27. Reidegeld K.A., Eisenacher M., Kohl M., Chamrad D., Körting G., Blüggel M. et al. (2008) An easy-to-use Decoy Database Builder software tool, implementing different decoy strategies for false discovery rate calculation in automated MS/MS protein identifications Proteomics 8, 1129-1137.
28. Elias J.E. and Gygi S.P. (2007) Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry Nat Methods 4, 207-214.
29. Shilov I.V., Seymour S.L., Patel A.A., Loboda A., Tang W.H., Keating S.P. et al. (2007) The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra Mol Cell Proteomics 6, 1638-1655.
30. Käll L., Storey J.D., MacCoss M.J. and Noble W.S. (2008) Assigning significance to peptides identified by tandem mass spectrometry using decoy databases J Proteome Res 7, 29-34.
31. Käll L., Storey J.D., MacCoss M.J. and Noble W.S. (2008) Posterior error probabilities and false discovery rates: Two sides of the same coin J Proteome Res 7, 40-44.
32. Pevtsov S., Fedulova I., Mirzaei H., Buck C. and Zhang X. (2006) Performance evaluation of existing de novo sequencing algorithms J Proteome Res 5, 3018-3028.
33. Pitzer E., Masselot A. and Colinge J. (2007) Assessing peptide de novo sequencing algorithms performance on large and diverse data sets Proteomics 7, 3051-3054.
34. Kim S., Bandeira N. and Pevzner P.A. (2009) Spectral profiles, a novel representation of tandem mass spectra and their applications for de novo peptide sequencing and identification Mol Cell Proteomics 8, 1391-1400.
35. Mann M. and Wilm M. (1994) Error-tolerant identification of peptides in sequence databases by peptide sequence tags Anal Chem 66, 4390-4399.
36. Tabb D.L., Saraf A. and Yates J.R. (2003) GutenTag: High-throughput sequence tagging via an empirically derived fragmentation model Anal Chem 75, 6415-6421.
37. Dasari S., Chambers M.C., Slebos R.J., Zimmerman L.J., Ham A.L. and Tabb D.L. (2010) TagRecon: High-throughput mutation identification through sequence tagging J Proteome Res 9, 1716-1726.
38. Nesvizhskii A.I. and Aebersold R. (2005) Interpretation of shotgun proteomic data: The protein inference problem Mol Cell Proteomics 4, 1419-1440.
39. Zhang B., Chambers M.C. and Tabb D.L. (2007) Proteomic parsimony through bipartite graph analysis improves accuracy and transparency J Proteome Res 6, 3549-3557.
40. Nesvizhskii A.I., Keller A., Kolker E. and Aebersold R. (2003) A statistical model for identifying proteins by tandem mass spectrometry Anal Chem 75, 4646-4658.
41. Ma Z., Dasari S., Chambers M.C., Litton M.D., Sobecki S.M., Zimmerman L.J. et al. (2009) IDPicker 2.0: Improved protein assembly with high discrimination peptide identification filtering J Proteome Res 8, 3872-3881.
42. Martens L., Muller M., Stephan C., Hamacher M., Reidegeld K.A., Meyer H.E. et al. (2006) A comparison of the HUPO Brain Proteome Project pilot with other proteomics studies Proteomics 6, 5076-5086.
43. Fenselau C. (2007) A review of quantitative methods for proteomic studies. J Chromatogr B Analyt Technol Biomed Life Sci 855, 14-20.
44. Bantscheff M., Schirle M., Sweetman G., Rick J. and Kuster B. (2007) Quantitative mass spectrometry in proteomics: A critical review Anal Bioanal Chem 389, 1017-1031.
45. Nakamura T. and Oda Y. (2007) Mass spectrometry-based quantitative proteomics Biotechnol Genet Eng Rev 24, 147-163.
46. Mueller L.N., Brusniak M., Mani D.R. and Aebersold R. (2008) An assessment of software solutions for the analysis of mass spectrometry based quantitative proteomics data J Proteome Res 7, 51-61.
47. Jin S., Daly D.S., Springer D.L. and Miller J.H. (2008) The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS J Proteome Res 7, 164-169.
48. Zhang Y., Wen Z., Washburn M.P. and Florens L. (2010) Refinements to label free proteome quantitation: How to deal with peptides shared by multiple proteins Anal Chem 82, 2272-2281.
49. Colaert N., Helsens K., Impens F., Vandekerckhove J. and Gevaert K. (2010) Rover: A tool to visualize and validate quantitative proteomics data from different sources Proteomics 10, 1226-1229.
50. Muth T., Keller D., Puetz S.M., Martens L., Sickmann A. and Boehm A.M. (2010) jTraqX: A free, platform independent tool for isobaric tag quantitation at the protein level Proteomics 10, 1223-1225.
51. Lange V., Picotti P., Domon B. and Aebersold R. (2008) Selected reaction monitoring for quantitative proteomics: A tutorial Mol Syst Biol 4, 222.
52. Walsh G.M., Lin S., Evans D.M., Khosrovi-Eghbal A., Beavis R.C. and Kast J. (2009) Implementation of a data repository-driven approach for targeted proteomics experiments by multiple reaction monitoring J Proteomics 72, 838-852.
53. Sherwood C.A., Eastham A., Lee L.W., Peterson A., Eng J.K., Shteynberg D. et al. (2009) MaRiMba: A software application for spectral library-based MRM transition list assembly J Proteome Res 8, 4396-4405.
54. Mead J.A., Bianco L., Ottone V., Barton C., Kay R.G., Lilley K.S. et al. (2009) MRMaid, the web-based tool for designing multiple reaction monitoring (MRM) transitions Mol Cell Proteomics 8, 696-705.