Amino Acids

, Volume 44, Issue 4, pp 1129–1137 | Cite as

Crowdsourcing in proteomics: public resources lead to better experiments

  • Harald Barsnes
  • Lennart MartensEmail author
Invited Review


With the growing interest in the field of proteomics, the amount of publicly available proteome resources has also increased dramatically. This means that there are many useful resources available for almost all aspects of a proteomics experiment. However, it remains vital to use the right resource, for the right purpose, at the right time. This review is therefore meant to aid the reader in obtaining an overview of the available resources and their application, thus providing the necessary background to choose the appropriate resources for the experiment at hand. Many of the resources are also taking advantage of so-called crowdsourcing to maximize the potential of the resource. What this means and how this can improve future experiments will also be discussed. The text roughly follows the steps involved in a proteomics experiment, starting with the planning of the experiment, via the processing of the data and the analysis of the results, to the community-wide sharing of the produced data.


Proteomics Mass spectrometry Bioinformatics Databases Repositories 



H.B. is supported by the Research Council of Norway, and L.M. acknowledges the support of Ghent University (Multidisciplinary Research Partnership “Bioinformatics: from nucleotides to networks”), and the PRIME-XS and ProteomeXchange projects, grant agreement numbers 262067 and 260558, both funded by the European Union 7th Framework Program.


  1. Abbatiello SE, Mani DR, Keshishian H, Carr SA (2010) Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry. Clin Chem 56(2):291–305. doi: 10.1373/clinchem.2009.138420 PubMedCrossRefGoogle Scholar
  2. Aebersold R, Mann M (2003) Mass spectrometry-based proteomics. Nature 422:198–207PubMedCrossRefGoogle Scholar
  3. Barsnes H, Vizcaíno JA, Eidhammer I, Martens L (2009) PRIDE Converter: making proteomics data-sharing easy. Nat Biotechnol 27(7):598–599PubMedCrossRefGoogle Scholar
  4. Barsnes H, Eidhammer I, Martens L (2010) Fragmentation analyzer: an open-source tool to analyze MS/MS fragmentation data. Proteomics 10(5):1087–1090PubMedGoogle Scholar
  5. Barsnes H, Vaudel M, Colaert N, Helsens K, Sickmann A, Berven FS, Martens L (2011) Compomics-utilities: an open-source Java library for computational proteomics. BMC Bioinformatics 12:70. doi: 10.1186/1471-2105-12-70 PubMedCrossRefGoogle Scholar
  6. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The Protein Data Bank. Nucleic Acids Res 28(1):235–242. doi: gkd090 PubMedCrossRefGoogle Scholar
  7. Bern M, Kil YJ (2011) Comment on unbiased statistical analysis for multi-stage proteomic search strategies. J Proteome Res 10(4):2123–2127. doi: 10.1021/pr101143m PubMedCrossRefGoogle Scholar
  8. Binns D, Dimmer E, Huntley R, Barrell D, O’Donovan C, Apweiler R (2009) QuickGO: a web-based tool for gene ontology searching. Bioinformatics 25(22):3045–3046. doi: 10.1093/bioinformatics/btp536 PubMedCrossRefGoogle Scholar
  9. Brusniak MY, Kwok ST, Christiansen M, Campbell D, Reiter L, Picotti P, Kusebauch U, Ramos H, Deutsch EW, Chen J, Moritz RL, Aebersold R (2011) ATAQS: a computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry. BMC Bioinformatics 12:78. doi: 10.1186/1471-2105-12-78 PubMedCrossRefGoogle Scholar
  10. Colaert N, Degroeve S, Helsens K, Martens L (2011) Analysis of the resolution limitations of peptide identification algorithms. J Proteome Res 10(12):5555–5561. doi: 10.1021/pr200913a PubMedCrossRefGoogle Scholar
  11. Colinge J, Masselot A, Carbonell P, Appel RD (2006) InSilicoSpectro: an open-source proteomics library. J Proteome Res 5(3):619–624. doi: 10.1021/pr0504236 PubMedCrossRefGoogle Scholar
  12. Côté RG, Jones P, Martens L, Kerrien S, Reisinger F, Lin Q, Leinonen R, Apweiler R, Hermjakob H (2007) The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases. BMC Bioinformatics 8:401PubMedCrossRefGoogle Scholar
  13. Cottrell JS (1994) Protein identification by peptide mass fingerprinting. Pept Res 7(3):115–124PubMedGoogle Scholar
  14. Craig R, Cortens JP, Beavis RC (2004) Open source system for analyzing, validating, and storing protein identification data. J Proteome Res 3(6):1234–1242. doi: 10.1021/pr049882h PubMedCrossRefGoogle Scholar
  15. Craig R, Cortens JP, Beavis RC (2005) The use of proteotypic peptide libraries for protein identification. Rapid Commun Mass Spectrom 19(13):1844–1850. doi: 10.1002/rcm.1992 PubMedCrossRefGoogle Scholar
  16. Creasy DM, Cottrell JS (2002) Error tolerant searching of uninterpreted tandem mass spectrometry data. Proteomics 2(10):1426–1434. doi: 10.1002/1615-9861(200210)2:10<1426:AID-PROT1426>3.0.CO;2-5 PubMedCrossRefGoogle Scholar
  17. da Huang W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44–57. doi: 10.1038/nprot.2008.211 CrossRefGoogle Scholar
  18. Desiere F, Deutsch EW, King NL, Nesvizhskii AI, Mallick P, Eng J, Chen S, Eddes J, Loevenich SN, Aebersold R (2006) The PeptideAtlas project. Nucleic Acids Res 34(Database issue):D655–D658. doi: 10.1093/nar/gkj040 PubMedCrossRefGoogle Scholar
  19. Deutsch EW, Lam H, Aebersold R (2008) PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows. EMBO Rep 9(5):429–434. doi: 10.1038/embor.2008.56 PubMedCrossRefGoogle Scholar
  20. Deutsch EW, Chambers M, Neumann S, Levander F, Binz PA, Shofstahl J, Campbell DS, Mendoza L, Ovelleiro D, Helsens K, Martens L, Aebersold R, Moritz RL, Brusniak MY (2011) TraML: a standard format for exchange of selected reaction monitoring transition lists. Mol Cell Proteomics. doi: 10.1074/mcp.R111.015040 Google Scholar
  21. Domon B, Aebersold R (2006) Mass spectrometry and protein analysis. Science 312(5771):212–217. doi: 10.1126/science.1124619 PubMedCrossRefGoogle Scholar
  22. Editors (2007) Democratizing proteomics data. Nat Biotechnol 25(3):262Google Scholar
  23. Editors (2008) Thou shalt share your data. Nat Methods 5(3):209CrossRefGoogle Scholar
  24. Eisenacher M (2011) mzIdentML: an open community-built standard format for the results of proteomics spectrum identification algorithms. Methods Mol Biol 696:161–177. doi: 10.1007/978-1-60761-987-1_10 PubMedCrossRefGoogle Scholar
  25. Eisenacher M, Martens L, Hardt T, Kohl M, Barsnes H, Helsens K, Häkkinen J, Levander F, Aebersold R, Vandekerckhove J, Dunn MJ, Lisacek F, Siepen JA, Hubbard SJ, Binz PA, Blüggel M, Thiele H, Cottrell J, Meyer HE, Apweiler R, Stephan C (2009) Getting a grip on proteomics data—proteomics data collection (ProDaC). Proteomics 9(15):3928–3933PubMedCrossRefGoogle Scholar
  26. Eng J, McCormack AL, Yates JR III (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(11):976–989CrossRefGoogle Scholar
  27. Everett LJ, Bierl C, Master SR (2010) Unbiased statistical analysis for multi-stage proteomic search strategies. J Proteome Res 9(2):700–707. doi: 10.1021/pr900256v PubMedCrossRefGoogle Scholar
  28. Fenyo D, Beavis RC (2003) A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes. Anal Chem 75(4):768–774PubMedCrossRefGoogle Scholar
  29. Flicek P, Amode MR, Barrell D, Beal K, Brent S, Chen Y, Clapham P, Coates G, Fairley S, Fitzgerald S, Gordon L, Hendrix M, Hourlier T, Johnson N, Kahari A, Keefe D, Keenan S, Kinsella R, Kokocinski F, Kulesha E, Larsson P, Longden I, McLaren W, Overduin B, Pritchard B, Riat HS, Rios D, Ritchie GR, Ruffier M, Schuster M, Sobral D, Spudich G, Tang YA, Trevanion S, Vandrovcova J, Vilella AJ, White S, Wilder SP, Zadissa A, Zamora J, Aken BL, Birney E, Cunningham F, Dunham I, Durbin R, Fernandez-Suarez XM, Herrero J, Hubbard TJ, Parker A, Proctor G, Vogel J, Searle SM (2011) Ensembl 2011. Nucleic Acids Res 39(Database issue):D800–D806. doi: 10.1093/nar/gkq1064 PubMedCrossRefGoogle Scholar
  30. Foster JM, Degroeve S, Gatto L, Visser M, Wang R, Griss J, Apweiler R, Martens L (2011) A posteriori quality control for the curation and reuse of public proteomics data. Proteomics 11(11):2182–2194. doi: 10.1002/pmic.201000602 PubMedCrossRefGoogle Scholar
  31. Frank AM, Savitski MM, Nielsen ML, Zubarev RA, Pevzner PA (2007) De novo peptide sequencing and identification with precision mass spectrometry. J Proteome Res 6(1):114–123PubMedCrossRefGoogle Scholar
  32. Gallien S, Duriez E, Domon B (2011) Selected reaction monitoring applied to proteomics. J Mass Spectrom 46(3):298–312. doi: 10.1002/jms.1895 PubMedCrossRefGoogle Scholar
  33. Geer LY, Markey SP, Kowalak JA, Wagner L, Xu M, Maynard DM, Yang X, Shi W, Bryant SH (2004) Open mass spectrometry search algorithm. J Proteome Res 3(5):958–964PubMedCrossRefGoogle Scholar
  34. Gevaert K, Van Damme J, Goethals M, Thomas GR, Hoorelbeke B, Demol H, Martens L, Puype M, Staes A, Vandekerckhove J (2002) Chromatographic isolation of methionine-containing peptides for gel-free proteome analysis: identification of more than 800 Escherichia coli proteins. Mol Cell Proteomics 1(11):896–903PubMedCrossRefGoogle Scholar
  35. Gevaert K, Goethals M, Martens L, Van Damme J, Staes A, Thomas GR, Vandekerckhove J (2003) Exploring proteomes and analyzing protein processing by mass spectrometric identification of sorted N-terminal peptides. Nat Biotechnol 21(5):566–569. doi: 10.1038/nbt810 PubMedCrossRefGoogle Scholar
  36. Gevaert K, Ghesquiere B, Staes A, Martens L, Van Damme J, Thomas GR, Vandekerckhove J (2004) Reversible labeling of cysteine-containing peptides allows their specific chromatographic isolation for non-gel proteome studies. Proteomics 4(4):897–908. doi: 10.1002/pmic.200300641 PubMedCrossRefGoogle Scholar
  37. Griss J, Cote RG, Gerner C, Hermjakob H, Vizcaino JA (2011a) Published and perished? The influence of the searched protein database on the long-term storage of proteomics data. Mol Cell Proteomics 10 (9):M111 008490. doi: 10.1074/mcp.M111.008490
  38. Griss J, Martin M, O’Donovan C, Apweiler R, Hermjakob H, Vizcaino JA (2011b) Consequences of the discontinuation of the International Protein Index (IPI) database and its substitution by the UniProtKB complete proteome sets. Proteomics 11(22):4434–4438. doi: 10.1002/pmic.201100363 PubMedCrossRefGoogle Scholar
  39. Guberman JM, Ai J, Arnaiz O, Baran J, Blake A, Baldock R, Chelala C, Croft D, Cros A, Cutts RJ, Di Genova A, Forbes S, Fujisawa T, Gadaleta E, Goodstein DM, Gundem G, Haggarty B, Haider S, Hall M, Harris T, Haw R, Hu S, Hubbard S, Hsu J, Iyer V, Jones P, Katayama T, Kinsella R, Kong L, Lawson D, Liang Y, Lopez-Bigas N, Luo J, Lush M, Mason J, Moreews F, Ndegwa N, Oakley D, Perez-Llamas C, Primig M, Rivkin E, Rosanoff S, Shepherd R, Simon R, Skarnes B, Smedley D, Sperling L, Spooner W, Stevenson P, Stone K, Teague J, Wang J, Whitty B, Wong DT, Wong-Erasmus M, Yao L, Youens-Clark K, Yung C, Zhang J, Kasprzyk A (2011) BioMart Central Portal: an open database network for the biological community. Database (Oxford) 2011:bar041. doi: 10.1093/database/bar041
  40. Haider S, Ballester B, Smedley D, Zhang J, Rice P, Kasprzyk A (2009) BioMart Central Portal–unified access to biological data. Nucleic Acids Res 37(Web Server issue):W23–W27. doi: 10.1093/nar/gkp265 PubMedCrossRefGoogle Scholar
  41. Hamady M, Cheung TH, Tufo H, Knight R (2005) Does protein structure influence trypsin miscleavage? Using structural properties to predict the behavior of related proteins. IEEE Eng Med Biol Mag 24(3):58–66PubMedCrossRefGoogle Scholar
  42. Helsens K, Mueller M, Hulstaert N, Martens L (2012) Sigpep: Calculating unique peptide signature transition sets in a complete proteome background. Proteomics (in press)Google Scholar
  43. Hunter S, Jones P, Mitchell A, Apweiler R, Attwood TK, Bateman A, Bernard T, Binns D, Bork P, Burge S, de Castro E, Coggill P, Corbett M, Das U, Daugherty L, Duquenne L, Finn RD, Fraser M, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, McMenamin C, Mi H, Mutowo-Muellenet P, Mulder N, Natale D, Orengo C, Pesseat S, Punta M, Quinn AF, Rivoire C, Sangrador-Vegas A, Selengut JD, Sigrist CJ, Scheremetjew M, Tate J, Thimmajanarthanan M, Thomas PD, Wu CH, Yeats C, Yong SY (2012) InterPro in 2011: new developments in the family and domain prediction database. Nucleic Acids Res 40(Database issue):D306–D312. doi: 10.1093/nar/gkr948 PubMedCrossRefGoogle Scholar
  44. Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M (2012) KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 40(Database issue):D109–D114. doi: 10.1093/nar/gkr988 PubMedCrossRefGoogle Scholar
  45. Karp NA, Lilley KS (2009) Investigating sample pooling strategies for DIGE experiments to address biological variability. Proteomics 9(2):388–397. doi: 10.1002/pmic.200800485 PubMedCrossRefGoogle Scholar
  46. Kasprzyk A (2011) BioMart: driving a paradigm change in biological data management. Database (Oxford) 2011:bar049. doi: 10.1093/database/bar049
  47. Kerrien S, Aranda B, Breuza L, Bridge A, Broackes-Carter F, Chen C, Duesbury M, Dumousseau M, Feuermann M, Hinz U, Jandrasits C, Jimenez RC, Khadake J, Mahadevan U, Masson P, Pedruzzi I, Pfeiffenberger E, Porras P, Raghunath A, Roechert B, Orchard S, Hermjakob H (2012) The IntAct molecular interaction database in 2012. Nucleic Acids Res 40(Database issue):D841–D846. doi: 10.1093/nar/gkr1088 PubMedCrossRefGoogle Scholar
  48. Kersey PJ, Duarte J, Williams A, Karavidopoulou Y, Birney E, Apweiler R (2004) The International Protein Index: an integrated database for proteomics experiments. Proteomics 4(7):1985–1988. doi: 10.1002/pmic.200300721 PubMedCrossRefGoogle Scholar
  49. Lam H (2011) Building and searching tandem mass spectral libraries for peptide identification. Mol Cell Proteomics 10 (12):R111 008565. doi: 10.1074/mcp.R111.008565
  50. Lange V, Malmstrom JA, Didion J, King NL, Johansson BP, Schafer J, Rameseder J, Wong CH, Deutsch EW, Brusniak MY, Buhlmann P, Bjorck L, Domon B, Aebersold R (2008a) Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring. Mol Cell Proteomics 7(8):1489–1500. doi: 10.1074/mcp.M800032-MCP200 PubMedCrossRefGoogle Scholar
  51. Lange V, Picotti P, Domon B, Aebersold R (2008b) Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol 4 (222): EpubGoogle Scholar
  52. Levin Y (2011) The role of statistical power analysis in quantitative proteomics. Proteomics 11(12):2565–2567. doi: 10.1002/pmic.201100033 PubMedCrossRefGoogle Scholar
  53. Ma B, Johnson R (2012) De novo sequencing and homology searching. Mol Cell Proteomics 11(2):O111.014902. doi: 10.1074/mcp.O111.014902
  54. MacLean B, Tomazela DM, Shulman N, Chambers M, Finney GL, Frewen B, Kern R, Tabb DL, Liebler DC, MacCoss MJ (2010) Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26(7):966–968. doi: 10.1093/bioinformatics/btq054 PubMedCrossRefGoogle Scholar
  55. Mallick P, Schirle M, Chen SS, Flory MR, Lee H, Martin D, Ranish J, Raught B, Schmitt R, Werner T, Kuster B, Aebersold R (2007) Computational prediction of proteotypic peptides for quantitative proteomics. Nat Biotechnol 25(1):125–131. doi: 10.1038/nbt1275 PubMedCrossRefGoogle Scholar
  56. Martens L (2011) Proteomics databases and repositories. Methods Mol Biol 694:213–227. doi: 10.1007/978-1-60761-977-2_14 PubMedCrossRefGoogle Scholar
  57. Martens L, Hermjakob H (2007) Proteomics data validation: why all must provide data. Mol BioSyst 3(8):518–522. doi: 10.1039/b705178f PubMedCrossRefGoogle Scholar
  58. Martens L, Vandekerckhove J, Gevaert K (2005) DBToolkit: processing protein databases for peptide-centric proteomics. Bioinformatics 21(17):3584–3585PubMedCrossRefGoogle Scholar
  59. Martens L, Orchard S, Apweiler R, Hermjakob H (2007) Human Proteome Organization Proteomics Standards Initiative: data standardization, a view on developments and policy. Mol Cell Proteomics 6 (9):1666–1667. 6/9/1666 [pii]Google Scholar
  60. Martens L, Chambers M, Sturm M, Kessner D, Levander F, Shofstahl J, Tang WH, Rompp A, Neumann S, Pizarro AD, Montecchi-Palazzi L, Tasman N, Coleman M, Reisinger F, Souda P, Hermjakob H, Binz PA, Deutsch EW (2011) mzML–a community standard for mass spectrometry data. Mol Cell Proteomics 10 (1):R110 000133. doi: 10.1074/mcp.R110.000133 Google Scholar
  61. Matthews L, Gopinath G, Gillespie M, Caudy M, Croft D, de Bono B, Garapati P, Hemish J, Hermjakob H, Jassal B, Kanapin A, Lewis S, Mahajan S, May B, Schmidt E, Vastrik I, Wu G, Birney E, Stein L, D’Eustachio P (2009) Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res 37(Database issue):D619–D622. doi: 10.1093/nar/gkn863 PubMedCrossRefGoogle Scholar
  62. Mueller M, Vizcaino JA, Jones P, Cote R, Thorneycroft D, Apweiler R, Hermjakob H, Martens L (2008) Analysis of the experimental detection of central nervous system-related genes in human brain and cerebrospinal fluid datasets. Proteomics 8(6):1138–1148. doi: 10.1002/pmic.200700761 PubMedCrossRefGoogle Scholar
  63. Na S, Bandeira N, Paek E (2012) Fast multi-blind modification search through tandem mass spectrometry. Mol Cell Proteomics 11 (4):M111 010199. doi: 10.1074/mcp.M111.010199
  64. Nesvizhskii AI, Aebersold R (2005) Interpretation of shotgun proteomic data: the protein inference problem. Mol Cell Proteomics 4(10):1419–1440PubMedCrossRefGoogle Scholar
  65. Nilsson T, Mann M, Aebersold R, Yates JR 3rd, Bairoch A, Bergeron JJ (2010) Mass spectrometry in high-throughput proteomics: ready for the big time. Nat Methods 7(9):681–685. doi: 10.1038/nmeth0910-681 PubMedCrossRefGoogle Scholar
  66. Oberg AL, Vitek O (2009) Statistical design of quantitative mass spectrometry-based proteomic experiments. J Proteome Res 8(5):2144–2156. doi: 10.1021/pr8010099 PubMedCrossRefGoogle Scholar
  67. Orchard S, Albar JP, Deutsch EW, Eisenacher M, Vizcaino JA, Hermjakob H (2011) Enabling BioSharing - a report on the Annual Spring Workshop of the HUPO-PSI April 11–13, 2011, EMBL-Heidelberg, Germany. Proteomics 11(22):4284–4290. doi: 10.1002/pmic.201190117 PubMedCrossRefGoogle Scholar
  68. Picotti P, Rinner O, Stallmach R, Dautel F, Farrah T, Domon B, Wenschuh H, Aebersold R (2010) High-throughput generation of selected reaction-monitoring assays for proteins and proteomes. Nat Methods 7(1):43–46. doi: 10.1038/nmeth.1408 PubMedCrossRefGoogle Scholar
  69. Prlic A, Down TA, Hubbard TJ (2005) Adding some SPICE to DAS. Bioinformatics 21(Suppl 2):ii40–ii41. doi: 10.1093/bioinformatics/bti1106 PubMedCrossRefGoogle Scholar
  70. Pruitt KD, Tatusova T, Maglott DR (2007) NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res 35(Database issue):D61–D65. doi: 10.1093/nar/gkl842 PubMedCrossRefGoogle Scholar
  71. Reidegeld KA, Eisenacher M, Kohl M, Chamrad D, Korting G, Bluggel M, Meyer HE, Stephan C (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(6):1129–1137. doi: 10.1002/pmic.200701073 PubMedCrossRefGoogle Scholar
  72. Reisinger F, Martens L (2009) Database on demand—an online tool for the custom generation of FASTA-formatted sequence databases. Proteomics 9(18):4421–4424. doi: 10.1002/pmic.200900254 PubMedCrossRefGoogle Scholar
  73. Rodriguez J, Gupta N, Smith RD, Pevzner PA (2008) Does trypsin cut before proline? J Proteome Res 7(1):300–305. doi: 10.1021/pr0705035 PubMedCrossRefGoogle Scholar
  74. Sherman J, McKay MJ, Ashman K, Molloy MP (2009) Unique ion signature mass spectrometry, a deterministic method to assign peptide identity. Mol Cell Proteomics 8(9):2051–2062. doi: 10.1074/mcp.M800512-MCP200 PubMedCrossRefGoogle Scholar
  75. Sherwood CA, Eastham A, Lee LW, Risler J, Vitek O, Martin DB (2009) Correlation between y-type ions observed in ion trap and triple quadrupole mass spectrometers. J Proteome Res 8(9):4243–4251PubMedCrossRefGoogle Scholar
  76. Siepen JA, Keevil EJ, Knight D, Hubbard SJ (2007) Prediction of missed cleavage sites in tryptic peptides aids protein identification in proteomics. J Proteome Res 6(1):399–408. doi: 10.1021/pr060507u PubMedCrossRefGoogle Scholar
  77. Smedley D, Haider S, Ballester B, Holland R, London D, Thorisson G, Kasprzyk A (2009) BioMart—biological queries made easy. BMC Genomics 10:22. doi: 10.1186/1471-2164-10-22 PubMedCrossRefGoogle Scholar
  78. Swaney DL, Wenger CD, Coon JJ (2010) Value of using multiple proteases for large-scale mass spectrometry-based proteomics. J Proteome Res 9(3):1323–1329. doi: 10.1021/pr900863u PubMedCrossRefGoogle Scholar
  79. Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork P, Jensen LJ, von Mering C (2011) The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res 39(Database issue):D561–D568. doi: 10.1093/nar/gkq973 PubMedCrossRefGoogle Scholar
  80. Tabb DL, Saraf A, Yates JR 3rd (2003) GutenTag: high-throughput sequence tagging via an empirically derived fragmentation model. Anal Chem 75(23):6415–6421. doi: 10.1021/ac0347462 PubMedCrossRefGoogle Scholar
  81. Tabb DL, Ma ZQ, Martin DB, Ham AJ, Chambers MC (2008) DirecTag: accurate sequence tags from peptide MS/MS through statistical scoring. J Proteome Res 7(9):3838–3846. doi: 10.1021/pr800154p PubMedCrossRefGoogle Scholar
  82. Taylor CF (2006) Minimum reporting requirements for proteomics: a MIAPE primer. Proteomics 6(Suppl 2):39–44PubMedCrossRefGoogle Scholar
  83. Tharakan R, Edwards N, Graham DR (2010) Data maximization by multipass analysis of protein mass spectra. Proteomics 10(6):1160–1171. doi: 10.1002/pmic.200900433 PubMedCrossRefGoogle Scholar
  84. The call of the human proteome (2010) Nat. Methods 7(9):661Google Scholar
  85. Thiede B, Lamer S, Mattow J, Siejak F, Dimmler C, Rudel T, Jungblut PR (2000) Analysis of missed cleavage sites, tryptophan oxidation and N-terminal pyroglutamylation after in-gel tryptic digestion. Rapid Commun Mass Spectrom 14(6):496–502. doi: 10.1002/(SICI)1097-0231(20000331)14:6<496:AID-RCM899>3.0.CO;2-1 PubMedCrossRefGoogle Scholar
  86. UniProt Consortium (2010) The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res 38(Database issue):142–148CrossRefGoogle Scholar
  87. Van Damme P, Martens L, Van Damme J, Hugelier K, Staes A, Vandekerckhove J, Gevaert K (2005) Caspase-specific and nonspecific in vivo protein processing during Fas-induced apoptosis. Nat Methods 2(10):771–777. doi: 10.1038/nmeth792 PubMedCrossRefGoogle Scholar
  88. Vaudel M, Burkhart JM, Sickmann A, Martens L, Zahedi RP (2011) Peptide identification quality control. Proteomics 11(10):2105–2114. doi: 10.1002/pmic.201000704 PubMedCrossRefGoogle Scholar
  89. Villaveces JM, Jimenez RC, Garcia LJ, Salazar GA, Gel B, Mulder N, Martin M, Garcia A, Hermjakob H (2011) Dasty3, a WEB framework for DAS. Bioinformatics 27(18):2616–2617. doi: 10.1093/bioinformatics/btr433 PubMedGoogle Scholar
  90. Vizcaino JA, Martens L, Hermjakob H, Julian RK, Paton NW (2007) The PSI formal document process and its implementation on the PSI website. Proteomics 7(14):2355–2357. doi: 10.1002/pmic.200700064 PubMedCrossRefGoogle Scholar
  91. Vizcaino JA, Mueller M, Hermjakob H, Martens L (2009) Charting online OMICS resources: a navigational chart for clinical researchers. Proteomics Clin Appl 3(1):18–29. doi: 10.1002/prca.200800082 PubMedCrossRefGoogle Scholar
  92. Vizcaíno JA, Côté R, Reisinger F, Barsnes H, Foster JM, Rameseder J, Hermjakob H, Martens L (2010) The Proteomics Identifications database: 2010 update. Nucleic Acids Res 38(Database issue):736–742CrossRefGoogle Scholar
  93. Wang R, Fabregat A, Rios D, Ovelleiro D, Foster JM, Cote RG, Griss J, Csordas A, Perez-Riverol Y, Reisinger F, Hermjakob H, Martens L, Vizcaino JA (2012) PRIDE Inspector: a tool to visualize and validate MS proteomics data. Nat Biotechnol 30(2):135–137. doi: 10.1038/nbt.2112 PubMedCrossRefGoogle Scholar
  94. Woollard PM (2010) Asking complex questions of the genome without programming. Methods Mol Biol 628:39–52. doi: 10.1007/978-1-60327-367-1_3 PubMedCrossRefGoogle Scholar
  95. Yates JR III, Eng JK, McCormack AL, Schieltz D (1995) Method to correlate tandem mass spectra of modified peptides to amino acid sequences in the protein database. Anal Chem 67(8):1426–1436PubMedCrossRefGoogle Scholar
  96. Yen CY, Russell S, Mendoza AM, Meyer-Arendt K, Sun S, Cios KJ, Ahn NG, Resing KA (2006) Improving sensitivity in shotgun proteomics using a peptide-centric database with reduced complexity: protease cleavage and SCX elution rules from data mining of MS/MS spectra. Anal Chem 78(4):1071–1084. doi: 10.1021/ac051127f PubMedCrossRefGoogle Scholar
  97. Yen CY, Meyer-Arendt K, Eichelberger B, Sun S, Houel S, Old WM, Knight R, Ahn NG, Hunter LE, Resing KA (2009) A simulated MS/MS library for spectrum-to-spectrum searching in large scale identification of proteins. Mol Cell Proteomics 8(4):857–869PubMedCrossRefGoogle Scholar
  98. Yen CY, Houel S, Ahn NG, Old WM (2011) Spectrum-to-spectrum searching using a proteome-wide spectral library. Mol Cell Proteomics 10 (7):M111 007666. doi: 10.1074/mcp.M111.007666
  99. Zhang Z (2004) Prediction of low-energy collision-induced dissociation spectra of peptides. Anal Chem 76(14):3908–3922PubMedCrossRefGoogle Scholar
  100. Zhang Z (2005) Prediction of low-energy collision-induced dissociation spectra of peptides with three or more charges. Anal Chem 77(19):6364–6373PubMedCrossRefGoogle Scholar
  101. Zhang X, Li Y, Shao W, Lam H (2011) Understanding the improved sensitivity of spectral library searching over sequence database searching in proteomics data analysis. Proteomics 11(6):1075–1085. doi: 10.1002/pmic.201000492 PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2013

Authors and Affiliations

  1. 1.Proteomics Unit, Department of BiomedicineUniversity of BergenBergenNorway
  2. 2.Department of Medical Protein ResearchVIBGhentBelgium
  3. 3.Department of Biochemistry, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium

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