The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Open Source System for Analyzing, Validating, and Storing Protein Identification Data
Open accessAbstract
This paper describes an open-source system for analyzing, storing, and validating proteomics information derived from tandem mass spectrometry. It is based on a combination of data analysis servers, a user interface, and a relational database. The database was designed to store the minimum amount of information necessary to search and retrieve data obtained from the publicly available data analysis servers. Collectively, this system was referred to as the Global Proteome Machine (GPM). The components of the system have been made available as open source development projects. A publicly available system has been established, comprised of a group of data analysis servers and one main database server.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
Cited by
The Perseus computational platform for comprehensive analysis of (prote)omics data
Tyanova, S., Temu, T., Sinitcyn, P., Carlson, A., Hein, M. Y., Geiger, T., Mann, M., & Cox, J. (2016) · Nature Methods · doi:10.1038/nmeth.3901 · Cited by 8,803
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585
ProteomeXchange provides globally coordinated proteomics data submission and dissemination
Vizcaíno, J. A., Deutsch, E. W., Wang, R., Csordas, A., Reisinger, F., Ríos, D., Dianes, J. A., Sun, Z., Farrah, T., Bandeira, N., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2839 · Cited by 2,729
A draft map of the human proteome
Kim, M.-S., Pinto, S. M., Getnet, D., Nirujogi, R. S., Manda, S. S., Chaerkady, R., Madugundu, A. K., Kelkar, D. S., Isserlin, R., Jain, S., et al. (2014) · Nature · doi:10.1038/nature13302 · Cited by 2,198
The Proteomics Identifications (PRIDE) database and associated tools: status in 2013
Vizcaíno, J. A., Côté, R. G., Csordas, A., Dianes, J. A., Fabregat, A., Foster, J. M., Griss, J., Alpi, E., Birim, M., Contell, J., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1262 · Cited by 1,918
Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions
Picotti, P., & Aebersold, R. (2012) · Nature Methods · doi:10.1038/nmeth.2015 · Cited by 1,302
Peterson, A. C., Russell, J. D., Bailey, D. J., Westphall, M. S., & Coon, J. J. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o112.020131 · Cited by 1,288
Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins
Anderson, L., & Hunter, C. L. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500331-mcp200 · Cited by 1,230
Proteomics by Mass Spectrometry: Approaches, Advances, and Applications
Yates, J. R., Ruse, C. I., & Nakorchevsky, A. (2009) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-061008-124934 · Cited by 1,078
Interpretation of Shotgun Proteomic Data
Nesvizhskii, A. I., & Aebersold, R. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r500012-mcp200 · Cited by 1,025
Neuronal Activity Promotes Glioma Growth through Neuroligin-3 Secretion
Venkatesh, H. S., Johung, T. B., Caretti, V., Noll, A., Tang, Y., Nagaraja, S., Gibson, E. M., Mount, C. W., Polepalli, J., Mitra, S. S., et al. (2015) · Cell · doi:10.1016/j.cell.2015.04.012 · Cited by 963
Desiere, F. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj040 · Cited by 910
The ProteomeXchange consortium at 10 years: 2023 update
Deutsch, E. W., Bandeira, N., Perez-Riverol, Y., Sharma, V., Carver, J. J., Mendoza, L., Kundu, D. J., Wang, S., Bandla, C., Kamatchinathan, S., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1040 · Cited by 819
The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics
Pino, L. K., Searle, B. C., Bollinger, J. G., Nunn, B., MacLean, B., & MacCoss, M. J. (2020) · Mass Spectrometry Reviews · doi:10.1002/mas.21540 · Cited by 800
mzML—a Community Standard for Mass Spectrometry Data
Martens, L., Chambers, M., Sturm, M., Kessner, D., Levander, F., Shofstahl, J., Tang, W. H., Römpp, A., Neumann, S., Pizarro, A. D., et al. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r110.000133 · Cited by 745
The ProteomeXchange consortium in 2020: enabling ‘big data’ approaches in proteomics
Deutsch, E. W., Bandeira, N., Sharma, V., Perez-Riverol, Y., Carver, J. J., Kundu, D. J., García-Seisdedos, D., Jarnuczak, A. F., Hewapathirana, S., Pullman, B. S., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz984 · Cited by 697
Computational prediction of proteotypic peptides for quantitative proteomics
Mallick, P., Schirle, M., Chen, S. S., Flory, M. R., Lee, H., Martin, D., Ranish, J., Raught, B., Schmitt, R., Werner, T., et al. (2007) · Nature Biotechnology · doi:10.1038/nbt1275 · Cited by 695
Multiple evidence strands suggest that there may be as few as 19 000 human protein-coding genes
Ezkurdia, I., Juan, D., Rodriguez, J. M., Frankish, A., Diekhans, M., Harrow, J., Vazquez, J., Valencia, A., & Tress, M. L. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu309 · Cited by 549
Lam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K., King, N., Stein, S. E., & Aebersold, R. (2007) · PROTEOMICS · doi:10.1002/pmic.200600625 · Cited by 517
Wang, M., Herrmann, C. J., Simonovic, M., Szklarczyk, D., & von Mering, C. (2015) · PROTEOMICS · doi:10.1002/pmic.201400441 · Cited by 537
Kuzyk, M. A., Smith, D., Yang, J., Cross, T. J., Jackson, A. M., Hardie, D. B., Anderson, N. L., & Borchers, C. H. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800540-mcp200 · Cited by 515
Paxdb, a database of protein abundance averages across all three domains of life
Wang, M., Weiss, M., Simonovic, M., Haertinger, G., Schrimpf, S. P., Hengartner, M. O., & von Mering, C. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.014704 · Cited by 466
“Finally, GPMDB, PeptideAtlas and MOPED are repositories that have the additional aim of re-processing submitted raw data in a consistent way (14, 15, 17).”
MethodMultidimensional proteomics for cell biology
Larance, M., & Lamond, A. I. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3970 · Cited by 411
Scoring proteomes with proteotypic peptide probes
Kuster, B., Schirle, M., Mallick, P., & Aebersold, R. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1683 · Cited by 364
The human proteome project: current state and future direction
Legrain, P., Aebersold, R., Archakov, A., Bairoch, A., Bala, K., Beretta, L., Bergeron, J., Borchers, C. H., Corthals, G. L., Costello, C. E., et al. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.009993 · Cited by 352
Vidova, V., & Spacil, Z. (2017) · Analytica Chimica Acta · doi:10.1016/j.aca.2017.01.059 · Cited by 352
Recent advances in computer-aided drug design
Song, C. M., Lim, S. J., & Tong, J. C. (2009) · Briefings in Bioinformatics · doi:10.1093/bib/bbp023 · Cited by 344
Deutsch, E. W., Mendoza, L., Shteynberg, D., Slagel, J., Sun, Z., & Moritz, R. L. (2015) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.201400164 · Cited by 342
Fabian, M. R., Cieplak, M. K., Frank, F., Morita, M., Green, J., Srikumar, T., Nagar, B., Yamamoto, T., Raught, B., Duchaine, T. F., et al. (2011) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2149 · Cited by 329
Lee, D., Lal, N. K., Lin, Z.-J. D., Ma, S., Liu, J., Castro, B., Toruño, T., Dinesh-Kumar, S. P., & Coaker, G. (2020) · Nature Communications · doi:10.1038/s41467-020-15601-5 · Cited by 319
Reiter, L., Claassen, M., Schrimpf, S. P., Jovanovic, M., Schmidt, A., Buhmann, J. M., Hengartner, M. O., & Aebersold, R. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900317-mcp200 · Cited by 312
Using Annotated Peptide Mass Spectrum Libraries for Protein Identification
Craig, R., Cortens, J. C., Fenyo, D., & Beavis, R. C. (2006) · Journal of Proteome Research · doi:10.1021/pr0602085 · Cited by 301
Self-citationPRIDE: a public repository of protein and peptide identifications for the proteomics community
Jones, P. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj138 · Cited by 290
The Proteomics Identifications database: 2010 update
Vizcaíno, J. A., Côté, R., Reisinger, F., Barsnes, H., Foster, J. M., Rameseder, J., Hermjakob, H., & Martens, L. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkp964 · Cited by 286
Selected reaction monitoring applied to proteomics
Gallien, S., Duriez, E., & Domon, B. (2011) · Journal of Mass Spectrometry · doi:10.1002/jms.1895 · Cited by 286
CPTAC Assay Portal: a repository of targeted proteomic assays
the Clinical Proteomic Tumor Analysis Consortium (CPTAC), Whiteaker, J. R., Halusa, G. N., Hoofnagle, A. N., Sharma, V., MacLean, B., Yan, P., Wrobel, J. A., Kennedy, J., Mani, D. R., et al. (2014) · Nature Methods · doi:10.1038/nmeth.3002 · Cited by 223
Advances in targeted proteomics and applications to biomedical research
Shi, T., Song, E., Nie, S., Rodland, K. D., Liu, T., Qian, W., & Smith, R. D. (2016) · PROTEOMICS · doi:10.1002/pmic.201500449 · Cited by 257
Clinical potential of mass spectrometry-based proteogenomics
Zhang, B., Whiteaker, J. R., Hoofnagle, A. N., Baird, G. S., Rodland, K. D., & Paulovich, A. G. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-018-0135-7 · Cited by 210
Analysis of High Accuracy, Quantitative Proteomics Data in the MaxQB Database
Schaab, C., Geiger, T., Stoehr, G., Cox, J., & Mann, M. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.014068 · Cited by 164
Le Bihan, M.-C., Bigot, A., Jensen, S. S., Dennis, J. L., Rogowska-Wrzesinska, A., Lainé, J., Gache, V., Furling, D., Jensen, O. N., Voit, T., et al. (2012) · Journal of Proteomics · doi:10.1016/j.jprot.2012.09.008 · Cited by 153
Prakash, A., Tomazela, D. M., Frewen, B., MacLean, B., Merrihew, G., Peterman, S., & MacCoss, M. J. (2009) · Journal of Proteome Research · doi:10.1021/pr801028b · Cited by 147
Introns in UTRs: why we should stop ignoring them
Bicknell, A. A., Cenik, C., Chua, H. N., Roth, F. P., & Moore, M. J. (2012) · BioEssays · doi:10.1002/bies.201200073 · Cited by 133
I-DIRT, A General Method for Distinguishing between Specific and Nonspecific Protein Interactions
Tackett, A. J., DeGrasse, J. A., Sekedat, M. D., Oeffinger, M., Rout, M. P., & Chait, B. T. (2005) · Journal of Proteome Research · doi:10.1021/pr050225e · Cited by 131
Ezkurdia, I., del Pozo, A., Frankish, A., Rodriguez, J. M., Harrow, J., Ashman, K., Valencia, A., & Tress, M. L. (2012) · Molecular Biology and Evolution · doi:10.1093/molbev/mss100 · Cited by 89
LeDuc, R. D., Fellers, R. T., Early, B. P., Greer, J. B., Thomas, P. M., & Kelleher, N. L. (2014) · Journal of Proteome Research · doi:10.1021/pr401277r · Cited by 85
Deutsch, E. W., Sun, Z., Campbell, D., Kusebauch, U., Chu, C. S., Mendoza, L., Shteynberg, D., Omenn, G. S., & Moritz, R. L. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00500 · Cited by 80
Gravett, M. G., Thomas, A., Schneider, K. A., Reddy, A. P., Dasari, S., Jacob, T., Lu, X., Rodland, M., Pereira, L., Sadowsky, D. W., et al. (2007) · Journal of Proteome Research · doi:10.1021/pr060149v · Cited by 81
Lassman, M. E., McLaughlin, T. M., Somers, E. P., Stefanni, A. C., Chen, Z., Murphy, B. A., Bierilo, K. K., Flattery, A. M., Wong, K. K., Castro‐Perez, J. M., et al. (2012) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.5296 · Cited by 51
Preservation of the metaproteome: variability of protein preservation in ancient dental calculus
Mackie, M., Hendy, J., Lowe, A. D., Sperduti, A., Holst, M., Collins, M. J., & Speller, C. F. (2017) · STAR: Science & Technology of Archaeological Research · doi:10.1080/20548923.2017.1361629 · Cited by 35
Hao, Y., Colak, R., Teyra, J., Corbi-Verge, C., Ignatchenko, A., Hahne, H., Wilhelm, M., Kuster, B., Braun, P., Kaida, D., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.06.031 · Cited by 23
Unraveling the glycosylated immunopeptidome with HLA-Glyco
Bedran, G., Polasky, D. A., Hsiao, Y., Yu, F., da Veiga Leprevost, F., Alfaro, J. A., Cieslik, M., & Nesvizhskii, A. I. (2023) · Nature Communications · doi:10.1038/s41467-023-39270-2 · Cited by 15
Metadata
- Authors
- Craig, R., Cortens, J. P., & Beavis, R. C.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2004-10-22
- Volume
- 3
- Issue
- 6
- Pages
- 1234-1242
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2031095666
- Cited by
- 694
- References
- 1
- FWCI
- 11.12
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.