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Bioinformatics for LC-MS/MS-Based Proteomics

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LC-MS/MS in Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 658))

Abstract

Mass spectrometry instrumentation has continued to develop rapidly in the last two decades, enabled in part by advances in microelectronic hardware controllers and computerized control and data acquisition systems. The wealth and complexity of data produced by a modern instrument is such that the data can no longer be analyzed manually. Computerized data analysis has become de rigueur and the bioinformatics field has expanded to provide software applications for all aspects of the data analysis needed by LC-MS/MS. The bioinformatics field is evolving rapidly and software applications are continually being improved or replaced for existing applications as well as developed to support new types of experiments and analysis enabled by modern instrumentation. Entire books have been written on MS data analysis in proteomics but this review will be necessarily brief. In this chapter we will review the bioinformatics software applications available for different LC-MS/MS analysis tasks.

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References

  1. Thirkettle, C., and Morris, H. R. (1980) Computer-assisted sequencing of peptide mass spectra [proceedings]. Biochem. Soc. Trans. 8, 176–177.

    PubMed  CAS  Google Scholar 

  2. Johnson, R. S., and Biemann, K. (1989) Computer program (SEQPEP) to aid in the interpretation of high-energy collision tandem mass spectra of peptides. Biomed. Environ. Mass Spectrom. 18, 945–957.

    Article  PubMed  CAS  Google Scholar 

  3. Pillay, T. S. (1988) TURBOLYTIK: a peptide cleavage program for personal computers. Int. I. Bio-med. Comput. 22, 259–264.

    Article  CAS  Google Scholar 

  4. Lee, T. D., and Vemuri, S. (1990) MacProMass: a computer program to correlate mass spectral data to peptide and protein structures. Biomed. Environ. Mass Spectrom. 19, 639–645.

    Article  PubMed  CAS  Google Scholar 

  5. Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. (1990) Basic local alignment search tool. J. Mol. Biol. 215, 403–410.

    PubMed  CAS  Google Scholar 

  6. (2009) GenBank release notes. National Center for Biotechnology Information. http://ftp://ftp.ncbi.nih.gov/genbank/release.notes/

  7. Stults, J. T., Lai, J., McCune, S., and Wetzel, R. (1993) Simplification of high-energy collision spectra of peptides by amino-terminal derivatization. Anal. Chem. 65, 1703–1708.

    Article  PubMed  CAS  Google Scholar 

  8. Yates, J. R., 3rd, Eng, J. K., McCormack, A. L., and Schieltz, D. (1995) Method to correlate tandem mass spectra of modified peptides to amino acid sequences in the protein database. Anal. Chem. 67, 1426–1436.

    Article  PubMed  CAS  Google Scholar 

  9. Mann, M., and Wilm, M. (1994) Error-tolerant identification of peptides in sequence databases by peptide sequence tags. Anal. Chem. 66, 4390–4399.

    Article  PubMed  CAS  Google Scholar 

  10. Matthiesen, R., (ed.) (2007) Mass spectrometry data analysis in proteomics. Vol. 367. Humana Press, Totowa, NJ, USA.

    Google Scholar 

  11. Eidhammer, I., Flikka, K., Martens, L., and Mikalsen, S. (2007) Computational methods for mass spectrometry proteomics. Wiley, Chichester, UK.

    Google Scholar 

  12. Pedersen, S. K., Harry, J. L., Sebastian, L., Baker, J., Traini, M. D., McCarthy, J. T., Manoharan, A., Wilkins, M. R., Gooley, A. A., Righetti, P. G., Packer, N. H., Williams, K. L., and Herbert, B. R. (2003) Unseen proteome: mining below the tip of the iceberg to find low abundance and membrane proteins. J. Proteome Res. 2, 303–311.

    Article  PubMed  CAS  Google Scholar 

  13. Sidhu, K. S., Sangvanich, P., Brancia, F. L., Sullivan, A. G., Gaskell, S. J., Wolkenhaue, O., Oliver, S. G., and Hubbard, S. J. (2001) Proteomics 1, 1368–1377.

    Article  PubMed  CAS  Google Scholar 

  14. Matthiesen, R., Lundsgaard, M., Welinder, K. G., and Bauw, G. (2003) Interpreting peptide mass spectra by VEMS. Bioinformatics (Oxford, England) 19, 792–793.

    Article  CAS  Google Scholar 

  15. Cargile, B. J., and Stephenson, J. L., Jr. (2004) An alternative to tandem mass spectrometry: isoelectric point and accurate mass for the identification of peptides. Anal. Chem. 76, 267–275.

    Article  PubMed  CAS  Google Scholar 

  16. Cagney, G., Amiri, S., Premawaradena, T., Lindo, M., and Emili, A. (2003) In silico proteome analysis to facilitate proteomics experiments using mass spectrometry. Proteome Sci. 1, 5.

    Article  PubMed  Google Scholar 

  17. Matthiesen, R., Trelle, M. B., Hojrup, P., Bunkenborg, J., and Jensen, O. N. (2005) VEMS 3.0: algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins. J. Proteome Res. 4, 2338–2347.

    Article  PubMed  CAS  Google Scholar 

  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. Am. Soc. Mass Spectrom. 5, 976–989.

    Article  CAS  Google Scholar 

  19. 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.

    Article  PubMed  CAS  Google Scholar 

  20. Conrads, T. P., Anderson, G. A., Veenstra, T. D., Pasa-Tolic, L., and Smith, R. D. (2000) Utility of accurate mass tags for proteome-wide protein identification. Anal. Chem. 72, 3349–3354.

    Article  PubMed  CAS  Google Scholar 

  21. Strittmatter, E. F., Ferguson, P. L., Tang, K., and Smith, R. D. (2003) Proteome analyses using accurate mass and elution time peptide tags with capillary LC time-of-flight mass spectrometry. J. Am. Soc. Mass Spectrom. 14, 980–991.

    Article  PubMed  CAS  Google Scholar 

  22. Clauser, K. R., Baker, P., and Burlingame, A. L. (1999) Role of accurate mass measurement (+/–10 ppm) in protein identification strategies employing MS or MS/MS and database searching. Anal. Chem. 71, 2871–2882.

    Article  PubMed  CAS  Google Scholar 

  23. Mueller, L. N., Brusniak, M. Y., 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.

    Article  PubMed  CAS  Google Scholar 

  24. Monroe, M. E., Tolic, N., Jaitly, N., Shaw, J. L., Adkins, J. N., and Smith, R. D. (2007) VIPER: an advanced software package to support high-throughput LC-MS peptide identification. Bioinformatics (Oxford, England) 23, 2021–2023.

    Article  CAS  Google Scholar 

  25. Yen, C. Y., Meyer-Arendt, K., Eichelberger, B., Sun, S., Houel, S., Old, W. M., Knight, R., Ahn, N. G., Hunter, L. E., and Resing, K. A. (2009) A simulated MS/MS library for spectrum-to-spectrum searching in large scale identification of proteins. Mol. Cell. Proteomics 8, 857–869.

    Article  PubMed  CAS  Google Scholar 

  26. Anderson, D. C., Li, W., Payan, D. G., and Noble, W. S. (2003) A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: support vector machine classification of peptide MS/MS spectra and SEQUEST scores. J. Proteome Res. 2, 137–146.

    Article  PubMed  CAS  Google Scholar 

  27. Kall, L., Canterbury, J. D., Weston, J., Noble, W. S., and MacCoss, M. J. (2007) Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat. Methods 4, 923–925.

    Article  PubMed  CAS  Google Scholar 

  28. Brosch, M., Yu, L., Hubbard, T., and Choudhary, J. (2009) Accurate and sensitive peptide identification with Mascot Percolator. J. Proteome Res.

    Google Scholar 

  29. 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.

    Article  PubMed  CAS  Google Scholar 

  30. Searle, B. C., Turner, M., and Nesvizhskii, A. I. (2008) Improving sensitivity by probabilistically combining results from multiple MS/MS search methodologies. J. Proteome Res. 7, 245–253.

    Article  PubMed  CAS  Google Scholar 

  31. Washburn, M. P., Wolters, D., and Yates, J. R., 3rd (2001) Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat. Biotechnol. 19, 242–247.

    Article  PubMed  CAS  Google Scholar 

  32. Yang, C. G., Granite, S. J., Van Eyk, J. E., and Winslow, R. L. (2006) MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data. Proteomics 6, 5688–5693.

    Article  PubMed  CAS  Google Scholar 

  33. Helsens, K., Martens, L., Vandekerckhove, J., and Gevaert, K. (2007) MascotDatfile: an open-source library to fully parse and analyse MASCOT MS/MS search results. Proteomics 7, 364–366.

    Article  PubMed  CAS  Google Scholar 

  34. Grosse-Coosmann, F., Boehm, A. M., and Sickmann, A. (2005) Efficient analysis and extraction of MS/MS result data from Mascot result files. BMC Bioinformatics 6, 290.

    Article  PubMed  CAS  Google Scholar 

  35. Bradshaw, R. A., Burlingame, A. L., Carr, S., and Aebersold, R. (2006) Reporting protein identification data: the next generation of guidelines. Mol. Cell. Proteomics 5, 787–788.

    Article  PubMed  CAS  Google Scholar 

  36. Wilkins, M. R., Appel, R. D., Van Eyk, J. E., Chung, M. C., Gorg, A., Hecker, M., Huber, L. A., Langen, H., Link, A. J., Paik, Y. K., Patterson, S. D., Pennington, S. R., Rabilloud, T., Simpson, R. J., Weiss, W., and Dunn, M. J. (2006) Guidelines for the next 10 years of proteomics, Proteomics 6, 4–8.

    Article  PubMed  CAS  Google Scholar 

  37. Ong, S. E., and Mann, M. (2005) Mass spectrometry-based proteomics turns quantitative. Nat. Chem. Biol. 1, 252–262.

    Article  PubMed  CAS  Google Scholar 

  38. Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., Purkayastha, S., Juhasz, P., Martin, S., Bartlet-Jones, M., He, F., Jacobson, A., and Pappin, D. J. (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics 3, 1154–1169.

    Article  PubMed  CAS  Google Scholar 

  39. Thompson, A., Schafer, J., Kuhn, K., Kienle, S., Schwarz, J., Schmidt, G., Neumann, T., Johnstone, R., Mohammed, A. K., and Hamon, C. (2003) Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem. 75, 1895–1904.

    Article  PubMed  CAS  Google Scholar 

  40. Han, D. K., Eng, J., Zhou, H., and Aebersold, R. (2001) Quantitative profiling of differentiation-induced microsomal proteins using isotope-coded affinity tags and mass spectrometry. Nat. Biotechnol. 19, 946–951.

    Article  PubMed  CAS  Google Scholar 

  41. Hicks, W. A., Halligan, B. D., Slyper, R. Y., Twigger, S. N., Greene, A. S., and Olivier, M. (2005) Simultaneous quantification and identification using 18O labeling with an ion trap mass spectrometer and the analysis software application “ZoomQuant”. J. Am. Soc. Mass Spectrom. 16, 916–925.

    Article  PubMed  CAS  Google Scholar 

  42. Miyagi, M., and Rao, K. C. (2007) Proteolytic 18O-labeling strategies for quantitative proteomics. Mass Spectrom. Rev. 26, 121–136.

    Article  PubMed  CAS  Google Scholar 

  43. Gerber, S. A., Rush, J., Stemman, O., Kirschner, M. W., and Gygi, S. P. (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc. Natl. Acad. Sci. USA 100, 6940–6945.

    Article  PubMed  CAS  Google Scholar 

  44. Ong, S. E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., and Mann, M. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 1, 376–386.

    Article  PubMed  CAS  Google Scholar 

  45. Zhang, G., and Neubert, T. A. (2006) Automated comparative proteomics based on multiplex tandem mass spectrometry and stable isotope labeling. Mol. Cell. Proteomics 5, 401–411.

    PubMed  CAS  Google Scholar 

  46. Wang, W., Zhou, H., Lin, H., Roy, S., Shaler, T. A., Hill, L. R., Norton, S., Kumar, P., Anderle, M., and Becker, C. H. (2003) Quantification of proteins and metabolites by mass spectrometry without isotopic labeling or spiked standards. Anal. Chem. 75, 4818–4826.

    Article  PubMed  CAS  Google Scholar 

  47. Chelius, D., Zhang, T., Wang, G., and Shen, R. F. (2003) Global protein identification and quantification technology using two-dimensional liquid chromatography nanospray mass spectrometry. Anal. Chem. 75, 6658– 6665.

    Article  PubMed  CAS  Google Scholar 

  48. Radulovic, D., Jelveh, S., Ryu, S., Hamilton, T. G., Foss, E., Mao, Y., and Emili, A. (2004) Informatics platform for global proteomic profiling and biomarker discovery using liquid chromatography–tandem mass spectrometry. Mol. Cell. Proteomics 3, 984–997.

    Article  PubMed  CAS  Google Scholar 

  49. Silva, J. C., Denny, R., Dorschel, C. A., Gorenstein, M., Kass, I. J., Li, G. Z., McKenna, T., Nold, M. J., Richardson, K., Young, P., and Geromanos, S. (2005) Quantitative proteomic analysis by accurate mass retention time pairs. Anal. Chem. 77, 2187–2200.

    Article  PubMed  CAS  Google Scholar 

  50. Hughes, M. A., Silva, J. C., Geromanos, S. J., and Townsend, C. A. (2006) Quantitative proteomic analysis of drug-induced changes in mycobacteria. J. Proteome Res. 5, 54–63.

    Article  PubMed  CAS  Google Scholar 

  51. Cutillas, P. R., Geering, B., Waterfield, M. D., and Vanhaesebroeck, B. (2005) Quantification of gel-separated proteins and their phosphorylation sites by LC-MS using unlabeled internal standards: analysis of phosphoprotein dynamics in a B cell lymphoma cell line. Mol. Cell. Proteomics 4, 1038–1051.

    Article  PubMed  CAS  Google Scholar 

  52. Ishihama, Y., Oda, Y., Tabata, T., Sato, T., Nagasu, T., Rappsilber, J., and Mann, M. (2005) Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol. Cell. Proteomics 4, 1265–1272.

    Article  PubMed  CAS  Google Scholar 

  53. Silva, J. C., Gorenstein, M. V., Li, G. Z., Vissers, J. P., and Geromanos, S. J. (2006) Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition. Mol. Cell. Proteomics 5, 144–156.

    PubMed  CAS  Google Scholar 

  54. Creasy, D. M., and Cottrell, J. S. (2002) Error tolerant searching of uninterpreted tandem mass spectrometry data. Proteomics 2, 1426–1434.

    Article  PubMed  CAS  Google Scholar 

  55. Bandeira, N., Tsur, D., Frank, A., and Pevzner, P. A. (2007) Protein identification by spectral networks analysis. Proc. Natl. Acad. Sci. USA 104, 6140–6145.

    Article  PubMed  CAS  Google Scholar 

  56. Potthast, F., Gerrits, B., Hakkinen, J., Rutishauser, D., Ahrens, C. H., Roschitzki, B., Baerenfaller, K., Munton, R. P., Walther, P., Gehrig, P., Seif, P., Seeberger, P. H., and Schlapbach, R. (2007) The Mass Distance Fingerprint: a statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry. J. Chromatogr. 854, 173–182.

    Article  CAS  Google Scholar 

  57. Savitski, M. M., Nielsen, M. L., and Zubarev, R. A. (2006) ModifiComb, a new proteomic tool for mapping substoichiometric post-translational modifications, finding novel types of modifications, and fingerprinting complex protein mixtures. Mol. Cell. Proteomics 5, 935–948.

    Article  PubMed  CAS  Google Scholar 

  58. Beausoleil, S. A., Villen, J., Gerber, S. A., Rush, J., and Gygi, S. P. (2006) A probability-based approach for high-throughput protein phosphorylation analysis and site localization. Nat. Biotechnol. 24, 1285–1292.

    Article  PubMed  CAS  Google Scholar 

  59. Arntzen, M. O., Osland, C. L., Raa, C. R., Kopperud, R., Doskeland, S. O., Lewis, A. E., and D’Santos, C. S. (2009) POSTMan (POST-translational modification analysis), a software application for PTM discovery. Proteomics 9, 1400–1406.

    Article  PubMed  CAS  Google Scholar 

  60. Pearson, W. R. (1990) Rapid and sensitive sequence comparison with FASTP and FASTA. Methods Enzymol. 183, 63–98.

    Article  PubMed  CAS  Google Scholar 

  61. Hoaglund-Hyzer, C. S., Li, J., and Clemmer, D. E. (2000) Mobility labeling for parallel CID of ion mixtures. Anal. Chem. 72, 2737–2740.

    Article  PubMed  CAS  Google Scholar 

  62. Niggeweg, R., Kocher, T., Gentzel, M., Buscaino, A., Taipale, M., Akhtar, A., and Wilm, M. (2006) A general precursor ion-like scanning mode on quadrupole-TOF instruments compatible with chromatographic separation. Proteomics 6, 41–53.

    Article  PubMed  CAS  Google Scholar 

  63. Chalkley, R. J., Baker, P. R., Hansen, K. C., Medzihradszky, K. F., Allen, N. P., Rexach, M., and Burlingame, A. L. (2005) Comprehensive analysis of a multidimensional liquid chromatography mass spectrometry dataset acquired on a quadrupole selecting, quadrupole collision cell, time-of-flight mass spectrometer: I. How much of the data is theoretically interpretable by search engines? Mol. Cell. Proteomics 4, 1189–1193.

    Article  PubMed  CAS  Google Scholar 

  64. Vestal, M. L., Campbell, J. M., Hayden, K. M., Chen, X., Strahler, J. R., and Andrews, P. C. (2005) Dynamic range in MALDI TOF–TOF analysis of protein digests. In “53th ASMS conference on mass spectrometry, San Antonio, TX, USA”.

    Google Scholar 

  65. Bader, G. D., Donaldson, I., Wolting, C., Ouellette, B. F., Pawson, T., and Hogue, C. W. (2001) BIND―The Biomolecular Interaction Network Database. Nucleic Acids Res. 29, 242–245.

    Article  PubMed  CAS  Google Scholar 

  66. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., Harris, M. A., Hill, D. P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J. C., Richardson, J. E., Ringwald, M., Rubin, G. M., and Sherlock, G. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29.

    Article  PubMed  CAS  Google Scholar 

  67. Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., and Kanehisa, M. (1999) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 27, 29–34.

    Article  PubMed  CAS  Google Scholar 

  68. Wood, V., Gwilliam, R., Rajandream, M. A., Lyne, M., Lyne, R., Stewart, A., Sgouros, J., Peat, N., Hayles, J., Baker, S., Basham, D., Bowman, S., Brooks, K., Brown, D., Brown, S., Chillingworth, T., Churcher, C., Collins, M., Connor, R., Cronin, A., Davis, P., Feltwell, T., Fraser, A., Gentles, S., Goble, A., Hamlin, N., Harris, D., Hidalgo, J., Hodgson, G., Holroyd, S., Hornsby, T., Howarth, S., Huckle, E. J., Hunt, S., Jagels, K., James, K., Jones, L., Jones, M., Leather, S., McDonald, S., McLean, J., Mooney, P., Moule, S., Mungall, K., Murphy, L., Niblett, D., Odell, C., Oliver, K., O’Neil, S., Pearson, D., Quail, M. A., Rabbinowitsch, E., Rutherford, K., Rutter, S., Saunders, D., Seeger, K., Sharp, S., Skelton, J., Simmonds, M., Squares, R., Squares, S., Stevens, K., Taylor, K., Taylor, R. G., Tivey, A., Walsh, S., Warren, T., Whitehead, S., Woodward, J., Volckaert, G., Aert, R., Robben, J., Grymonprez, B., Weltjens, I., Vanstreels, E., Rieger, M., Schafer, M., Muller-Auer, S., Gabel, C., Fuchs, M., Dusterhoft, A., Fritzc, C., Holzer, E., Moestl, D., Hilbert, H., Borzym, K., Langer, I., Beck, A., Lehrach, H., Reinhardt, R., Pohl, T. M., Eger, P., Zimmermann, W., Wedler, H., Wambutt, R., Purnelle, B., Goffeau, A., Cadieu, E., Dreano, S., Gloux, S., Lelaure, V., Mottier, S., Galibert, F., Aves, S. J., Xiang, Z., Hunt, C., Moore, K., Hurst, S. M., Lucas, M., Rochet, M., Gaillardin, C., Tallada, V. A., Garzon, A., Thode, G., Daga, R. R., Cruzado, L., Jimenez, J., Sanchez, M., del Rey, F., Benito, J., Dominguez, A., Revuelta, J. L., Moreno, S., Armstrong, J., Forsburg, S. L., Cerutti, L., Lowe, T., McCombie, W. R., Paulsen, I., Potashkin, J., Shpakovski, G. V., Ussery, D., Barrell, B. G., and Nurse, P. (2002) The genome sequence of Schizosaccharomyces pombe. Nature 415, 871–880.

    Article  PubMed  CAS  Google Scholar 

  69. Drysdale, R. A., and Crosby, M. A. (2005) FlyBase: genes and gene models. Nucleic Acids Res. 33, D390–D395.

    Article  PubMed  CAS  Google Scholar 

  70. Piggee, C. (2008) LIMS and the art of MS proteomics. Anal. Chem. 80, 4801–4806.

    Article  PubMed  CAS  Google Scholar 

  71. Orchard, S., Hermjakob, H., and Apweiler, R. (2003) The proteomics standards initiative. Proteomics 3, 1374–1376.

    Article  PubMed  CAS  Google Scholar 

  72. Martens, L., Nesvizhskii, A. I., Hermjakob, H., Adamski, M., Omenn, G. S., Vandekerckhove, J., and Gevaert, K. (2005) Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories. Proteomics 5, 3501–3505.

    Article  PubMed  CAS  Google Scholar 

  73. Taylor, C. F., Paton, N. W., Lilley, K. S., Binz, P. A., Julian, R. K., Jr., Jones, A. R., Zhu, W., Apweiler, R., Aebersold, R., Deutsch, E. W., Dunn, M. J., Heck, A. J., Leitner, A., Macht, M., Mann, M., Martens, L., Neubert, T. A., Patterson, S. D., Ping, P., Seymour, S. L., Souda, P., Tsugita, A., Vandekerckhove, J., Vondriska, T. M., Whitelegge, J. P., Wilkins, M. R., Xenarios, I., Yates, J. R., 3rd, and Hermjakob, H. (2007) The minimum information about a proteomics experiment (MIAPE). Nat. Biotechnol. 25, 887–893.

    Article  PubMed  CAS  Google Scholar 

  74. Falkner, J. A., and Andrews, P. C. (2006) Open access, peer reviewed, peer-to-peer based proteomics data dissemination and archival system. In ABRF, Long Beach, CA, USA.

    Google Scholar 

  75. Desiere, F., Deutsch, E. W., King, N. L., Nesvizhskii, A. I., Mallick, P., Eng, J., Chen, S., Eddes, J., Loevenich, S. N., and Aebersold, R. (2006) The PeptideAtlas project. Nucleic Acids Res. 34, D655–D658.

    Article  PubMed  CAS  Google Scholar 

  76. Martens, L., Hermjakob, H., Jones, P., Adamski, M., Taylor, C., States, D., Gevaert, K., Vandekerckhove, J., and Apweiler, R. (2005) PRIDE: the proteomics identifications database. Proteomics 5, 3537–3545.

    Article  PubMed  CAS  Google Scholar 

  77. Keller, A., Eng, J., Zhang, N., Li, X. J., and Aebersold, R. (2005) A uniform proteomics MS/MS analysis platform utilizing open XML file formats. Mol. Syst. Biol. 1, 2005.0017.

    Article  PubMed  CAS  Google Scholar 

  78. Kessner, D., Chambers, M., Burke, R., Agus, D., and Mallick, P. (2008) ProteoWizard: open source software for rapid proteomics tools development. Bioinformatics (Oxford, England) 24, 2534–2536.

    Article  CAS  Google Scholar 

  79. Zhang, N., Aebersold, R., and Schwikowski, B. (2002) ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data. Proteomics 2, 1406–1412.

    Article  PubMed  CAS  Google Scholar 

  80. Geer, L. Y., Markey, S. P., Kowalak, J. A., Wagner, L., Xu, M., Maynard, D. M., Yang, X., Shi, W., and Bryant, S. H. (2004) Open mass spectrometry search algorithm. J. Proteome Res. 3, 958–964.

    Article  PubMed  CAS  Google Scholar 

  81. Heller, M., Ye, M., Michel, P. E., Morier, P., Stalder, D., Junger, M. A., Aebersold, R., Reymond, F., and Rossier, J. S. (2005) Added value for tandem mass spectrometry shotgun proteomics data validation through isoelectric focusing of peptides. J. Proteome Res. 4, 2273–2282.

    Article  PubMed  CAS  Google Scholar 

  82. Craig, R., and Beavis, R. C. (2004) TANDEM: matching proteins with tandem mass spectra. Bioinformatics (Oxford, England) 20, 1466–1467.

    Article  CAS  Google Scholar 

  83. Shilov, I. V., Seymour, S. L., Patel, A. A., Loboda, A., Tang, W. H., Keating, S. P., Hunter, C. L., Nuwaysir, L. M., and Schaeffer, D. A. (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.

    Article  PubMed  CAS  Google Scholar 

  84. 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.

    Article  PubMed  CAS  Google Scholar 

  85. Tabb, D. L., Saraf, A., and Yates, J. R., 3rd (2003) GutenTag: high-throughput sequence tagging via an empirically derived fragmentation model. Anal. Chem. 75, 6415–6421.

    Article  PubMed  CAS  Google Scholar 

  86. Tanner, S., Shu, H., Frank, A., Wang, L. C., Zandi, E., Mumby, M., Pevzner, P. A., and Bafna, V. (2005) InsPecT: identification of posttranslationally modified peptides from tandem mass spectra. Anal. Chem. 77, 4626–4639.

    Article  PubMed  CAS  Google Scholar 

  87. Wilkins, M. R., Gasteiger, E., Wheeler, C. H., Lindskog, I., Sanchez, J. C., Bairoch, A., Appel, R. D., Dunn, M. J., and Hochstrasser, D. F. (1998) Multiple parameter cross-species protein identification using MultiIdent―a world-wide web accessible tool. Electrophoresis 19, 3199–3206.

    Article  PubMed  CAS  Google Scholar 

  88. Han, Y., Ma, B., and Zhang, K. (2004) SPIDER: software for protein identification from sequence tags with de novo sequencing error. Proc./IEEE Comput. Syst. Bioinformatics Conf. CSB, 206–215.

    Google Scholar 

  89. Qin, J., Fenyo, D., Zhao, Y., Hall, W. W., Chao, D. M., Wilson, C. J., Young, R. A., and Chait, B. T. (1997) A strategy for rapid, high-confidence protein identification. Anal. Chem. 69, 3995–4001.

    Article  PubMed  CAS  Google Scholar 

  90. May, D., Fitzgibbon, M., Liu, Y., Holzman, T., Eng, J., Kemp, C. J., Whiteaker, J., Paulovich, A., and McIntosh, M. (2007) A platform for accurate mass and time analyses of mass spectrometry data. J. Proteome Res. 6, 2685–2694.

    Article  PubMed  CAS  Google Scholar 

  91. Lam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K., King, N., Stein, S. E., and Aebersold, R. (2007) Development and validation of a spectral library searching method for peptide identification from MS/MS. Proteomics 7, 655–667.

    Article  PubMed  CAS  Google Scholar 

  92. Frewen, B., and MacCoss, M. J. (2007) Using BiblioSpec for creating and searching tandem MS peptide libraries. Current protocols in bioinformatics/editorial board, Andreas D. Baxevanis ... [et al Chapter 13, Unit 13.7].

    Google Scholar 

  93. Frank, A. M., Bandeira, N., Shen, Z., Tanner, S., Briggs, S. P., Smith, R. D., and Pevzner, P. A. (2008) Clustering millions of tandem mass spectra. J. Proteome Res. 7, 113–122.

    Article  PubMed  CAS  Google Scholar 

  94. Palagi, P. M., Walther, D., Quadroni, M., Catherinet, S., Burgess, J., Zimmermann-Ivol, C. G., Sanchez, J. C., Binz, P. A., Hochstrasser, D. F., and Appel, R. D. (2005) MSight: an image analysis software for liquid chromatography–mass spectrometry. Proteomics 5, 2381–2384.

    Article  PubMed  CAS  Google Scholar 

  95. Li, X. J., Pedrioli, P. G., Eng, J., Martin, D., Yi, E. C., Lee, H., and Aebersold, R. (2004) A tool to visualize and evaluate data obtained by liquid chromatography–electrospray ionization–mass spectrometry. Anal. Chem. 76, 3856–3860.

    Article  PubMed  CAS  Google Scholar 

  96. Gehlenborg, N., Yan, W., Lee, I. Y., Yoo, H., Nieselt, K., Hwang, D., Aebersold, R., and Hood, L. (2009) Prequips―an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data. Bioinformatics (Oxford, England) 25, 682–683.

    Article  CAS  Google Scholar 

  97. 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.

    Article  PubMed  CAS  Google Scholar 

  98. Tabb, D. L., McDonald, W. H., and Yates, J. R., 3rd (2002) DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics. J. Proteome Res. 1, 21–26.

    Article  PubMed  CAS  Google Scholar 

  99. Askenazi, M., Parikh, J. R., and Marto, J. A. (2009) mzAPI: a new strategy for efficiently sharing mass spectrometry data. Nat. Methods 6, 240–241.

    Article  PubMed  CAS  Google Scholar 

  100. Slotta, D. J., McFarland, M., Makusky, A., and Markey, S. (2007) P18-T MassSieve: a new tool for mass spectrometry-based proteomics. J. Biomol. Tech. 18, 7.

    Google Scholar 

  101. Hartler, J., Thallinger, G. G., Stocker, G., Sturn, A., Burkard, T. R., Korner, E., Rader, R., Schmidt, A., Mechtler, K., and Trajanoski, Z. (2007) MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data. BMC Bioinformatics 8, 197.

    Article  PubMed  CAS  Google Scholar 

  102. Hakkinen, J., Vincic, G., Mansson, O., Warell, K., and Levander, F. (2009) The Proteios Software Environment: an extensible multiuser platform for management and analysis of proteomics data. J. Proteome Res.

    Google Scholar 

  103. Andersen, J. S., Wilkinson, C. J., Mayor, T., Mortensen, P., Nigg, E. A., and Mann, M. (2003) Proteomic characterization of the human centrosome by protein correlation profiling. Nature 426, 570–574.

    Article  PubMed  CAS  Google Scholar 

  104. Cox, J., Matic, I., Hilger, M., Nagaraj, N., Selbach, M., Olsen, J. V., and Mann, M. (2009) A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat. Protoc 4, 698–705.

    Article  PubMed  CAS  Google Scholar 

  105. 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.

    Article  PubMed  CAS  Google Scholar 

  106. Shadforth, I. P., Dunkley, T. P., Lilley, K. S., and Bessant, C. (2005) i-Tracker: for quantitative proteomics using iTRAQ. BMC Genomics 6, 145.

    Article  PubMed  CAS  Google Scholar 

  107. Bouyssie, D., Gonzalez de Peredo, A., Mouton, E., Albigot, R., Roussel, L., Ortega, N., Cayrol, C., Burlet-Schiltz, O., Girard, J. P., and Monsarrat, B. (2007) Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells. Mol. Cell. Proteomics 6, 1621–1637.

    Article  PubMed  CAS  Google Scholar 

  108. Polpitiya, A. D., Qian, W. J., Jaitly, N., Petyuk, V. A., Adkins, J. N., Camp, D. G., 2nd, Anderson, G. A., and Smith, R. D. (2008) DAnTE: a statistical tool for quantitative analysis of -omics data. Bioinformatics (Oxford, England) 24, 1556–1558.

    Article  CAS  Google Scholar 

  109. Mason, C. J., Therneau, T. M., Eckel-Passow, J. E., Johnson, K. L., Oberg, A. L., Olson, J. E., Nair, K. S., Muddiman, D. C., and Bergen, H. R., 3rd (2007) A method for automatically interpreting mass spectra of 18O-labeled isotopic clusters. Mol. Cell. Proteomics 6, 305–318.

    PubMed  CAS  Google Scholar 

  110. van Breukelen, B., van den Toorn, H. W., Drugan, M. M., and Heck, A. J. (2009) StatQuant: A post quantification analysis toolbox for improving quantitative mass spectrometry. Bioinformatics (Oxford, England).

    Google Scholar 

  111. Potthast, F., Ocenasek, J., Rutishauser, D., Pelikan, M., and Schlapbach, R. (2005) Database independent detection of isotopically labeled MS/MS spectrum peptide pairs. J. Chromatogr. 817, 225–230.

    Article  CAS  Google Scholar 

  112. Pevzner, P. A., Mulyukov, Z., Dancik, V., and Tang, C. L. (2001) Efficiency of database search for identification of mutated and modified proteins via mass spectrometry. Genome Res. 11, 290–299.

    Article  PubMed  CAS  Google Scholar 

  113. Maclean, D., Burrell, M. A., Studholme, D. J., and Jones, A. M. (2008) PhosCalc: a tool for evaluating the sites of peptide phosphorylation from mass spectrometer data. BMC Res. Notes 1, 30.

    Article  PubMed  CAS  Google Scholar 

  114. Hernandez, P., Gras, R., Frey, J., and Appel, R. D. (2003) Popitam: towards new heuristic strategies to improve protein identification from tandem mass spectrometry data. Proteomics 3, 870–878.

    Article  PubMed  CAS  Google Scholar 

  115. Taylor, J. A., and Johnson, R. S. (2001) Implementation and uses of automated de novo peptide sequencing by tandem mass spectrometry. Anal. Chem. 73, 2594–2604.

    Article  PubMed  CAS  Google Scholar 

  116. Ma, B., Zhang, K., Hendrie, C., Liang, C., Li, M., Doherty-Kirby, A., and Lajoie, G. (2003) PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun. Mass Spectrom. 17, 2337–2342.

    Article  PubMed  CAS  Google Scholar 

  117. Fischer, B., Roth, V., Roos, F., Grossmann, J., Baginsky, S., Widmayer, P., Gruissem, W., and Buhmann, J. M. (2005) NovoHMM: a hidden Markov model for de novo peptide sequencing. Anal. Chem. 77, 7265–7273.

    Article  PubMed  CAS  Google Scholar 

  118. Grossmann, J., Roos, F. F., Cieliebak, M., Liptak, Z., Mathis, L. K., Muller, M., Gruissem, W., and Baginsky, S. (2005) AUDENS: a tool for automated peptide de novo sequencing. J. Proteome Res. 4, 1768–1774.

    Article  PubMed  CAS  Google Scholar 

  119. Alves, G., and Yu, Y. K. (2005) Robust accurate identification of peptides (RAId): deciphering MS2 data using a structured library search with de novo based statistics. Bioinformatics (Oxford, England) 21, 3726–3732.

    Article  CAS  Google Scholar 

  120. Dancik, V., Addona, T. A., Clauser, K. R., Vath, J. E., and Pevzner, P. A. (1999) De novo peptide sequencing via tandem mass spectrometry. J. Comput. Biol. 6, 327–342.

    Article  PubMed  CAS  Google Scholar 

  121. Frank, A., and Pevzner, P. (2005) PepNovo: de novo peptide sequencing via probabilistic network modeling. Anal. Chem. 77, 964–973.

    Article  PubMed  CAS  Google Scholar 

  122. Shevchenko, A. (2001) Evaluation of the efficiency of in-gel digestion of proteins by peptide isotopic labeling and MALDI mass spectrometry. Anal. Biochem. 296, 279–283.

    Article  PubMed  CAS  Google Scholar 

  123. Mackey, A. J., Haystead, T. A., and Pearson, W. R. (2002) Getting more from less: algorithms for rapid protein identification with multiple short peptide sequences. Mol. Cell. Proteomics 1, 139–147.

    Article  PubMed  CAS  Google Scholar 

  124. Zhang, N., Li, X. J., Ye, M., Pan, S., Schwikowski, B., and Aebersold, R. (2005) ProbIDtree: an automated software program capable of identifying multiple peptides from a single collision-induced dissociation spectrum collected by a tandem mass spectrometer. Proteomics 5, 4096–4106.

    Article  PubMed  CAS  Google Scholar 

  125. Hoopmann, M. R., Finney, G. L., and MacCoss, M. J. (2007) High-speed data reduction, feature detection, and MS/MS spectrum quality assessment of shotgun proteomics data sets using high-resolution mass spectrometry. Anal. Chem. 79, 5620–5632.

    Article  PubMed  CAS  Google Scholar 

  126. Olsen, J. V., Blagoev, B., Gnad, F., Macek, B., Kumar, C., Mortensen, P., and Mann, M. (2006) Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. Cell 127, 635–648.

    Article  PubMed  CAS  Google Scholar 

  127. Kersey, P., Bower, L., Morris, L., Horne, A., Petryszak, R., Kanz, C., Kanapin, A., Das, U., Michoud, K., Phan, I., Gattiker, A., Kulikova, T., Faruque, N., Duggan, K., McLaren, P., Reimholz, B., Duret, L., Penel, S., Reuter, I., and Apweiler, R. (2005) Integr8 and Genome Reviews: integrated views of complete genomes and proteomes. Nucleic Acids Res. 33, D297–D302.

    Article  PubMed  CAS  Google Scholar 

  128. Hao, P., He, W. Z., Huang, Y., Ma, L. X., Xu, Y., Xi, H., Wang, C., Liu, B. S., Wang, J. M., Li, Y. X., and Zhong, Y. (2005) MPSS: an integrated database system for surveying a set of proteins. Bioinformatics (Oxford, England) 21, 2142–2143.

    Article  CAS  Google Scholar 

  129. Carvalho, P. C., Fischer, J. S., Chen, E. I., Domont, G. B., Carvalho, M. G., Degrave, W. M., Yates, J. R., 3rd, and Barbosa, V. C. (2009) GO Explorer: a gene-ontology tool to aid in the interpretation of shotgun proteomics data. Proteome Sci. 7, 6.

    Article  PubMed  CAS  Google Scholar 

  130. Barrell, D., Dimmer, E., Huntley, R. P., Binns, D., O’Donovan, C., and Apweiler, R. (2009) The GOA database in 2009―an integrated Gene Ontology Annotation resource. Nucleic Acids Res. 37, D396–D403.

    Article  PubMed  CAS  Google Scholar 

  131. Prince, J. T., Carlson, M. W., Wang, R., Lu, P., and Marcotte, E. M. (2004) The need for a public proteomics repository. Nat. Biotechnol. 22, 471–472.

    Article  PubMed  CAS  Google Scholar 

  132. Mathivanan, S., Ahmed, M., Ahn, N. G., Alexandre, H., Amanchy, R., Andrews, P. C., Bader, J. S., Balgley, B. M., Bantscheff, M., Bennett, K. L., Bjorling, E., Blagoev, B., Bose, R., Brahmachari, S. K., Burlingame, A. S., Bustelo, X. R., Cagney, G., Cantin, G. T., Cardasis, H. L., Celis, J. E., Chaerkady, R., Chu, F., Cole, P. A., Costello, C. E., Cotter, R. J., Crockett, D., DeLany, J. P., De Marzo, A. M., DeSouza, L. V., Deutsch, E. W., Dransfield, E., Drewes, G., Droit, A., Dunn, M. J., Elenitoba-Johnson, K., Ewing, R. M., Van Eyk, J., Faca, V., Falkner, J., Fang, X., Fenselau, C., Figeys, D., Gagne, P., Gelfi, C., Gevaert, K., Gimble, J. M., Gnad, F., Goel, R., Gromov, P., Hanash, S. M., Hancock, W. S., Harsha, H. C., Hart, G., Hays, F., He, F., Hebbar, P., Helsens, K., Hermeking, H., Hide, W., Hjerno, K., Hochstrasser, D. F., Hofmann, O., Horn, D. M., Hruban, R. H., Ibarrola, N., James, P., Jensen, O. N., Jensen, P. H., Jung, P., Kandasamy, K., Kheterpal, I., Kikuno, R. F., Korf, U., Korner, R., Kuster, B., Kwon, M. S., Lee, H. J., Lee, Y. J., Lefevre, M., Lehvaslaiho, M., Lescuyer, P., Levander, F., Lim, M. S., Lobke, C., Loo, J. A., Mann, M., Martens, L., Martinez-Heredia, J., McComb, M., McRedmond, J., Mehrle, A., Menon, R., Miller, C. A., Mischak, H., Mohan, S. S., Mohmood, R., Molina, H., Moran, M. F., Morgan, J. D., Moritz, R., Morzel, M., Muddiman, D. C., Nalli, A., Navarro, J. D., Neubert, T. A., Ohara, O., Oliva, R., Omenn, G. S., Oyama, M., Paik, Y. K., Pennington, K., Pepperkok, R., Periaswamy, B., Petricoin, E. F., Poirier, G. G., Prasad, T. S., Purvine, S. O., Rahiman, B. A., Ramachandran, P., Ramachandra, Y. L., Rice, R. H., Rick, J., Ronnholm, R. H., Salonen, J., Sanchez, J. C., Sayd, T., Seshi, B., Shankari, K., Sheng, S. J., Shetty, V., Shivakumar, K., Simpson, R. J., Sirdeshmukh, R., Siu, K. W., Smith, J. C., Smith, R. D., States, D. J., Sugano, S., Sullivan, M., Superti-Furga, G., Takatalo, M., Thongboonkerd, V., Trinidad, J. C., Uhlen, M., Vandekerckhove, J., Vasilescu, J., Veenstra, T. D., Vidal-Taboada, J. M., Vihinen, M., Wait, R., Wang, X., Wiemann, S., Wu, B., Xu, T., Yates, J. R., Zhong, J., Zhou, M., Zhu, Y., Zurbig, P., and Pandey, A. (2008) Human Proteinpedia enables sharing of human protein data. Nat. Biotechnol. 26, 164–167.

    Article  PubMed  CAS  Google Scholar 

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Jacob, R.J. (2010). Bioinformatics for LC-MS/MS-Based Proteomics. In: Cutillas, P., Timms, J. (eds) LC-MS/MS in Proteomics. Methods in Molecular Biology, vol 658. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-780-8_4

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