Recent developments in public proteomic MS repositories and pipelines

Proteomics

Volumn 9, Issue 4, 2009, Pages 861-881

  Mead, Jennifer A ^a   Bianco, Luca ^a   Bessant, Conrad ^a  

^a CRANFIELD UNIVERSITY   (United Kingdom)

Author keywords

Bioinformatics; Data mining; Open access; Peptide identification pipelines; Proteomic repositories

Indexed keywords

BIOINFORMATICS; DATA ANALYSIS; NONHUMAN; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN DATABASE; PROTEOMICS; QUANTITATIVE STUDY; QUESTIONNAIRE; REVIEW; TANDEM MASS SPECTROMETRY;

ACCESS TO INFORMATION; ANIMALS; COMPUTATIONAL BIOLOGY; DATABASE MANAGEMENT SYSTEMS; DATABASES, PROTEIN; HUMANS; INFORMATION STORAGE AND RETRIEVAL; INTERNET; MASS SPECTROMETRY; PEPTIDES; PROTEINS; PROTEOMICS;

EID: 61349182486     PISSN: 16159853     EISSN: 16159861     Source Type: Journal    
DOI: 10.1002/pmic.200800553     Document Type: Review

References (71)

1. Mead, J. A., Shadforth, I. P., Bessant, C., Public proteomic MS repositories and pipelines: available tools and biological applications. Proteomics 2007, 7, 2769-2786.
2. Garden, P., Alm, R., Hakkinen, J., PROTEIOS: an open source proteomics initiative. Bioinformatics 2005, 21, 2085-2087.
3. Thomsen, A. L., Laukens, K., Matthiesen, R., Jensen, O. N., Organization of proteomics data with YassDB. Methods Mol. Biol. 2007, 367, 271-287.
4. Rauch, A., Bellew, M., Eng, J., Fitzgibbon, M. et al., Computational proteomics analysis system (CPAS): An extensible, open-source analytic system for evaluating and publishing proteomic data and high throughput biological experiments. J. Proteome Res. 2006, 5, 112-121.
5. Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D, et al., A systematic approach to modeling, capturing, and disseminating proteomics experimental data. Nat. Biotechnol. 2003, 21, 247-254.
6. Craig, R., Cortens, J. P., Beavis, R. C., The use of proteotypic peptide libraries for protein identification. Rapid Commun. Mass Spectrom. 2005, 19, 1844-1850.
7. Lange, V., Malmstrom, J., Didion, J., King, N. L. et al., Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring. Mol. Cell. Proteomics 2008, 7, 1489-1500.
8. Nesvizhskii, A. I., Vitek, O., Aebersold, R., Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat. Methods 2007, 4, 787-797.
9. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D. et al., Gene Ontology: tool for the unification of biology. Nat. Genet. 2000, 25, 25-29.
10. Jones, P., Côté, R. G., Martens, L., Quinn, A. F. et al., PRIDE: a public repository of protein and peptide identifications for the proteomics community. NAR 2006, 1, D659-663.
11. Craig, R., Cortens, J. P., Beavis, R. C., Open source system for analyzing, validating, and storing protein identification data. J. Proteome Res. 2004, 3, 1234-1242.
12. Desiere, F., Deutsch, E. W., King, N. L., Nesvizhskii, A. I. et al., The PeptideAtlas project. NAR 2006, 34, D655-D658.
13. Shadforth, I., Xu, W., Crowther, D., Bessant, C., GAPP: A fully automated software for the confident identification of human peptides from tandem mass spectra. J. Proteome Res. 2006, 5, 2849-2852.
14. Mathivanan, S., Ahmed, M., Ahn, N. G., Alexandre, H. et al., Human Proteinpedia enables sharing of human protein data. Nat. Biotechnol. 2008, 26, 164-165.
15. Zhang, Y., Zhang, Y., Adachi, J., Olsen, J.V. et al., MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes. Nucl. Acids Res. 2007, 35, D771-779.
16. Falth, M., Savitski, M. M., Nielsen, M. L., Kjeldsen, F. et al., SwedCAD, a database of annotated high-mass accuracy MS/MS spectra of tryptic peptides. J. Proteome Res. 2007, 6, 4063-4067.
17. McLaughlin, T., Siepen, J. A., Selley, J., Lynch, J. A. et al., PepSeeker: a database of proteome peptide identifications for investigating fragmentation patterns. Nucl. Acids Res. 2006, 34, D649-654.
18. Frewen, B., MacCoss, M. J., Using BiblioSpec for creating and searching tandem MS peptide libraries. Curr. Protoc. Bioinformatics 2007, 13.
19. Zhang, C., Crasta, O., Cammer, S., Will, R. et al., An emerging cyberinfrastructure for biodefense pathogen and pathogen host data. NAR 2008, 36, D884-891.
20. Hoogland, C., Mostaguir, K., Sanchez, J.-C., Hochstrasser, D. F., Appel, R. D., SWISS-2DPAGE, ten years later. Proteomics 2004, 4, 2352-2356.
21. Waters, M., Stasiewicz, S., Alex Merrick, B., Tomer, K. et al., CEBS chemical effects in biological systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. NAR 2008, 36, D892-900.
22. Jones, P., Côté, R. G., Cho, S. Y., Klie, S. et al., PRIDE: new developments and new datasets. NAR 2008, 36, D878-883.
23. Editorial, Democratizing proteomics data. Nat. Biotechnol. 2007, 25, 262.
24. Editorial, Thou shalt share your data. Nat. Methods 2008, 5, 209.
25. Deutsch, E. W., Lam, H., Aebersold, R., PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows EMBO Rep. 2008, 9, 429-434.
26. Dowell, R. D., Jokerst, R. M., Day, A., Eddy, S. R., Stein, L.,The distributed annotation system. BMC Bioinformatics 2001, 2, e-publication.
27. Shadforth, I., Bessant, C.,Genome annotating proteomics pipelines: available tools. Expert Rev. Proteomics 2006, 3.
28. Omenn, States, Adamski, Blackwell et al., Overview of the HUPO Plasma Proteome Project: Results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 2005, 5, 3226-3245.
29. Gortzak-Uzan, L., Ignatchenko, A., Evangelou, A. I., Agochiya, M. et al., A proteome resource of ovarian cancer ascites: Integrated proteomic and bioinformatic analyses to identify putative biomarkers. J. Proteome Res. 2008, 7, 339-351.
30. Mishra, G. R., Suresh, M., Kumaran, K., Kannabiran, N., et al., Human protein reference database-2006 update. NAR 2006, 1, D411-414.
31. Bairoch, A., Boeckmann, B., Ferro, S., Gasteiger, E., Swiss-Prot: Juggling between evolution and stability. Brief. Bioinform. 2004, 5, 39-55.
32. Adkins, J. N., Varnum, S. M., Auberry, K. J., Moore, R. J. et al., Toward a human blood serum proteome: Analysis by multidimensional separation coupled with mass spectrometry. Mol. Cell. Proteomics 2002, 1, 947-955.
33. Côté, R. G., Jones, P., Apweiler, R., Hermjakob, H., The ONTOLOGY lookup service, a lightweight cross-platform tool for controlled vocabulary queries. BMC Bioinformatics 2006, 28, 97.
34. Hartler, J., Thallinger, G. G., Stocker, G., Sturn, A. et al., MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data. BMC Bioinformatics 2007, 13, 197.
35. Siepen, J. A., Swainston, N., Jones, A. R., Hart, S. R. et al., An informatic pipeline for the data capture and submission of quantitative proteomic data using iTRAQTM. Proteome Sci. 2007, 1, 4.
36. Siepen, J. A., Belhajjame, K., Selley, J. N., Embury, S. M. et al., ISPIDER Central: an integrated database web-server for proteomics. NAR 2008, Epub, gkn196.
37. McDonald, W. H., Tabb, D. L., Sadygov, R. G., MacCoss, M. J. et al., MS1, MS2, and SQT-three unified, compact, and easily parsed file formats for the storage of shotgun proteomic spectra and identifications. Rapid Commun. Mas Spectrom. 2004, 18, 2162-2168.
38. Côté, R. G., Jones, P., Martens, L., Kerrien, S. et al., The protein identifier cross-referencing (PICR) service: reconciling protein identifiers across multiple source databases. BMC Bioinformatics 2007, 18, 401.
39. Krokhin, O. V., Craig, R., Spicer, V., Ens, W. et al., An improved model for prediction of retention times of tryptic peptides in ion pair reversed-phase HPLC: Its application to protein peptide mapping by off-line HPLC-MALDI MS. Mol. Cell. Proteomics 2004, 3, 908-919.
40. Krogh, A., Larsson, B., von Heijne, G., Sonnhammer, E. L. L., Predicting transmembrane protein topology with a hidden markov model: application to complete genomes. J. Mol. Biol. 2001, 305, 567-580.
41. Shannon, P., Markiel, A., Ozier, O., Baliga, N. S. et al., Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13, 2498-2504.
42. GO Consortium. The Gene Ontology project in 2008. NAR 2008, 36, D440-444.
43. Keller, A., Purvine, S., Nesvizhskii, A. I., Stolyar, S. et al., Experimental protein mixture for validating tandem mass spectral analysis. Omics J. Integrative Biol. 2002, 6, 207-212.
44. Klimek, J., Eddes, J. S., Hohmann, L., Jackson, J. et al., The standard protein mix database: A diverse data set to assist in the production of improved peptide and protein identification software tools. J. Proteome Res. 2008, 7, 96-103.
45. Falkner, J. A., Kachman, M., Veine, D. M., Walker, A. et al., Validated MALDI-TOF/TOF mass spectra for protein standards. J. Am. Soc. Mass Spectrom. 2007, 18, 850-855.
46. Craig, R., Cortens, J. C., Fenyo, D., Beavisa, R. C., Using annotated peptide mass spectrum libraries for protein identification. J. Proteome Res. 2006, 5, 1843-1849.
47. Eng, J. K., McCormack, A. L., Yates, J. R. r., An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 1994, 5, 976-989.
48. Craig, R., Beavis, R. C., A method for reducing the time required to match protein sequences with tandem mass spectra. Rapid Commun. Mass Spectrom. 2003, 17, 2310-2316.
49. Keller, A., Eng, J., Zhang, N., Li, X.-J., Aebersold, R., A uniform proteomics MS/MS analysis platform utilizing open XML file formats. Mol. Syst. Biol. 2005, 1, E1-E8.
50. Nesvizhskii, A., Keller, A., Kolker, E., Aebersold, R., A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 2003, 75, 4646-4658.
51. Lam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K. et al., Development and validation of a spectral library searching method for peptide identification from MS/MS. Proteomics 2007, 7, 655-667.
52. Sturm, M., Bertsch, A., Gröpl, C., Hildebrandt, A. et al., OpenMS - an open-source software framework for mass spectrometry. BMC Bioinformatics 2008, 9, 163-174.
53. Kohlbacher, O., Reinert, K., Gropl, C., Lange, E. et al., TOPP-the OpenMS proteomics pipeline. Bioinformatics 2007, 23, e191-197.
54. Hummel, J., Niemann, M., Wienkoop, S., Schulze, W. et al., ProMEX: a mass spectral reference database for proteins and protein phosphorylation sites. BMC Bioinformatics 2007, 8, 216-224.
55. Wolski, W. E., Lalowski, M., Martus, P., Herwig, R. et al., Transformation and other factors of the peptide mass spectrometry pairwise peak-list comparison process. BMC Bioinformatics 2006, 6, 285.
56. Geer, L. Y., Markey, S. P., Kowalak, J. A., Wagner, L. et al., Open mass spectrometry search algorithm. J. Proteome Res. 2004, 3, 958-964.
57. Balgley, B. M., Laudeman, T., Yang, L., Song, T., Lee, C. S., Comparative evaluation of tandem MS search algorithms using a target-decoy search strategy. Mol. Cell. Proteomics 2007, 6, 1599-1608.
58. Gerber, S. A., Rush, J., Stemman, O., Kirschner, M. W., Gygi, S. P., Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc. Natl. Acad. Sci. USA 2003, 100, 6940-6945.
59. Kuhn, E., Wu, J., Karl, J., Liao, H. et al., Quantification of C-reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C-labeled peptide standards. Proteomics 2004, 4, 1175-1186.
60. Anderson, L., Hunter, C. L., Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins. Mol. Cell. Proteomics 2006, 5, 573-588.
61. Mallick, P., Schirle, M., Chen, S. S., Flory, M. R. et al., Computational prediction of proteotypic peptides for quantitative proteomics. Nat. Biotechnol. 2007, 25, 125-131.
62. Tang, H., Arnold, R. J., Alves, P., Xun, Z. et al., A computational approach toward label-free protein quantification using predicted peptide detectability. Bioinformatics 2006, 22, e481-488.
63. Lau, K. W., Jones, A. R., Swainston, N., Siepen, J. A., Hubbard, S. J., Capture and analysis of quantitative proteomic data. Proteomics 2007, 7, 2787-2799.
64. Han, D. K., Eng, J., Zhou, H., Aebersold, R., Quantitative profiling of differentiation-induced microsomal proteins using isotope-coded affinity tags and mass spectrometry. Nat. Biotechnol. 2001, 79, 946-951.
65. Li, X. J., Zhang, H., Ranish, J. A., Aebersold, R., Automated statistical analysis of protein abundance ratios from data generated by stable-isotope dilution and tandem mass spectrometry. Anal. Chem. 2003, 75, 6648-6657.
66. Shadforth, I., Dunkley, T., Lilley, K., Bessant, C., i-Tracker: For quantitative proteomics using iTRAQTM. BMC Genomics 2005, 6, 145.
67. Hermjakob, H., Apweiler, R., The proteomics identifications database (PRIDE) and the ProteomExchange consortium: making proteomics data accessible. Expert Rev. Proteomics 2006, 3, 1-3.
68. Elias, J. E., Gygi, S. P., Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 2007, 4, 207-214.
69. Nesvizhskii, A. I., Roos, F. F., Grossmann, J., Vogelzang, M. et al., Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: Toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides. Mol. Cell. Proteomics 2006, 5, 652-670.
70. Taylor, G. K., Goodlett, D. R., Rules governing protein identification by mass spectrometry. Rapid Commun. Mas Spectrom. 2005, 19, 3420.
71. Mead, J. A., Bianco, L., Ottone, V., Barton, C., et al., MRMaid: the web-based tool for designing multiple reaction monitoring (MRM) transitions. Mol. Cell. Proteomics 2008, [Epub ahead of print].