Bioinformatics support for high-throughput proteomics

Wilke A, Rückert C, Bartels D, Dondrup M, Goesmann A, Hüser AT, Kespohl S, Linke B, Mahne M, McHardy A, Pühler A, et al. (2003)
JOURNAL OF BIOTECHNOLOGY 106(2-3): 147-156.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Wilke, A.; Rückert, ChristianUniBi ; Bartels, D.; Dondrup, M; Goesmann, AlexanderUniBi ; Hüser, A. T.; Kespohl, S.; Linke, B.; Mahne, M.; McHardy, A.; Pühler, AlfredUniBi ; Meyer, F.
Abstract / Bemerkung
In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteome data. The rapid advancement of this technique in combination with other methods used in proteomics results in an increasing number of high-throughput projects. This leads to an increasing amount of data that needs to be archived and analyzed. To cope with the need for automated data conversion, storage, and analysis in the field of proteomics, the open source system ProDB was developed. The system handles data conversion from different mass spectrometer software, automates data analysis, and allows the annotation of MS spectra (e.g. assign gene names, store data on protein modifications). The system is based on an extensible relational database to store the mass spectra together with the experimental setup. It also provides a graphical user interface (GUI) for managing the experimental steps which led to the MS data. Furthermore, it allows the integration of genome and proteome data. Data from an ongoing experiment was used to compare manual and automated analysis. First tests showed that the automation resulted in a significant saving of time. Furthermore, the quality and interpretability of the results was improved in all cases. (C) 2003 Elsevier B.V. All rights reserved.
Stichworte
automated analysis; platform; proteomics; archival of data
Erscheinungsjahr
2003
Zeitschriftentitel
JOURNAL OF BIOTECHNOLOGY
Band
106
Ausgabe
2-3
Seite(n)
147-156
ISSN
0168-1656
Page URI
https://pub.uni-bielefeld.de/record/1609272

Zitieren

Wilke A, Rückert C, Bartels D, et al. Bioinformatics support for high-throughput proteomics. JOURNAL OF BIOTECHNOLOGY. 2003;106(2-3):147-156.
Wilke, A., Rückert, C., Bartels, D., Dondrup, M., Goesmann, A., Hüser, A. T., Kespohl, S., et al. (2003). Bioinformatics support for high-throughput proteomics. JOURNAL OF BIOTECHNOLOGY, 106(2-3), 147-156. https://doi.org/10.1016/j.jbiotec.2003.08.009
Wilke, A., Rückert, Christian, Bartels, D., Dondrup, M, Goesmann, Alexander, Hüser, A. T., Kespohl, S., et al. 2003. “Bioinformatics support for high-throughput proteomics”. JOURNAL OF BIOTECHNOLOGY 106 (2-3): 147-156.
Wilke, A., Rückert, C., Bartels, D., Dondrup, M., Goesmann, A., Hüser, A. T., Kespohl, S., Linke, B., Mahne, M., McHardy, A., et al. (2003). Bioinformatics support for high-throughput proteomics. JOURNAL OF BIOTECHNOLOGY 106, 147-156.
Wilke, A., et al., 2003. Bioinformatics support for high-throughput proteomics. JOURNAL OF BIOTECHNOLOGY, 106(2-3), p 147-156.
A. Wilke, et al., “Bioinformatics support for high-throughput proteomics”, JOURNAL OF BIOTECHNOLOGY, vol. 106, 2003, pp. 147-156.
Wilke, A., Rückert, C., Bartels, D., Dondrup, M., Goesmann, A., Hüser, A.T., Kespohl, S., Linke, B., Mahne, M., McHardy, A., Pühler, A., Meyer, F.: Bioinformatics support for high-throughput proteomics. JOURNAL OF BIOTECHNOLOGY. 106, 147-156 (2003).
Wilke, A., Rückert, Christian, Bartels, D., Dondrup, M, Goesmann, Alexander, Hüser, A. T., Kespohl, S., Linke, B., Mahne, M., McHardy, A., Pühler, Alfred, and Meyer, F. “Bioinformatics support for high-throughput proteomics”. JOURNAL OF BIOTECHNOLOGY 106.2-3 (2003): 147-156.

15 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

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Schatschneider S, Schneider J, Blom J, Létisse F, Niehaus K, Goesmann A, Vorhölter FJ., Microbiology 163(8), 2017
PMID: 28795660
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Nebrich G, Herrmann M, Hartl D, Diedrich M, Kreitler T, Wierling C, Klose J, Giavalisco P, Zabel C, Mao L., Proteomics 9(7), 2009
PMID: 19259999
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Stenuit B, Eyers L, Schuler L, Agathos SN, George I., Biotechnol Adv 26(6), 2008
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Kaltenbach HM, Wilke A, Böcker S., BMC Bioinformatics 8(), 2007
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Hartler J, Thallinger GG, Stocker G, Sturn A, Burkard TR, Körner E, Rader R, Schmidt A, Mechtler K, Trajanoski Z., BMC Bioinformatics 8(), 2007
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MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data.
Yang CG, Granite SJ, Van Eyk JE, Winslow RL., Proteomics 6(21), 2006
PMID: 17006878
PROTICdb: a web-based application to store, track, query, and compare plant proteome data.
Ferry-Dumazet H, Houel G, Montalent P, Moreau L, Langella O, Negroni L, Vincent D, Lalanne C, de Daruvar A, Plomion C, Zivy M, Joets J., Proteomics 5(8), 2005
PMID: 15846840
BRIGEP--the BRIDGE-based genome-transcriptome-proteome browser.
Goesmann A, Linke B, Bartels D, Dondrup M, Krause L, Neuweger H, Oehm S, Paczian T, Wilke A, Meyer F., Nucleic Acids Res 33(web server issue), 2005
PMID: 15980569
PEDRo: a database for storing, searching and disseminating experimental proteomics data.
Garwood K, McLaughlin T, Garwood C, Joens S, Morrison N, Taylor CF, Carroll K, Evans C, Whetton AD, Hart S, Stead D, Yin Z, Brown AJ, Hesketh A, Chater K, Hansson L, Mewissen M, Ghazal P, Howard J, Lilley KS, Gaskell SJ, Brass A, Hubbard SJ, Oliver SG, Paton NW., BMC Genomics 5(), 2004
PMID: 15377392
Technology for high-throughput screens: the present and future using zebrafish.
Love DR, Pichler FB, Dodd A, Copp BR, Greenwood DR., Curr Opin Biotechnol 15(6), 2004
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EMMA: a platform for consistent storage and efficient analysis of microarray data.
Dondrup M, Goesmann A, Bartels D, Kalinowski J, Krause L, Linke B, Rupp O, Sczyrba A, Pühler A, Meyer F., J Biotechnol 106(2-3), 2003
PMID: 14651856

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