Bioinformatics support for high-throughput proteomics

被引:25
|
作者
Wilke, A [1 ]
Rückert, C
Bartels, D
Dondrup, M
Goesmann, A
Hüser, AT
Kespohl, S
Linke, B
Mahne, M
McHardy, A
Pühler, A
Meyer, F
机构
[1] Univ Bielefeld, Ctr Genome Res, D-33594 Bielefeld, Germany
[2] Univ Bielefeld, Int Grad Sch Bioinformat & Genome Res, D-33594 Bielefeld, Germany
[3] Univ Bielefeld, Dept Biol, Lehrstuhl Genet, D-33594 Bielefeld, Germany
关键词
proteomics; automated analysis; platform; archival of data;
D O I
10.1016/j.jbiotec.2003.08.009
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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.
引用
收藏
页码:147 / 156
页数:10
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