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2DDB - a bioinformatics solution for analysis of quantitative proteomics data.


ABSTRACT: BACKGROUND: We present 2DDB, a bioinformatics solution for storage, integration and analysis of quantitative proteomics data. As the data complexity and the rate with which it is produced increases in the proteomics field, the need for flexible analysis software increases. RESULTS: 2DDB is based on a core data model describing fundamentals such as experiment description and identified proteins. The extended data models are built on top of the core data model to capture more specific aspects of the data. A number of public databases and bioinformatical tools have been integrated giving the user access to large amounts of relevant data. A statistical and graphical package, R, is used for statistical and graphical analysis. The current implementation handles quantitative data from 2D gel electrophoresis and multidimensional liquid chromatography/mass spectrometry experiments. CONCLUSION: The software has successfully been employed in a number of projects ranging from quantitative liquid-chromatography-mass spectrometry based analysis of transforming growth factor-beta stimulated fi-broblasts to 2D gel electrophoresis/mass spectrometry analysis of biopsies from human cervix. The software is available for download at SourceForge.

SUBMITTER: Malmstrom L 

PROVIDER: S-EPMC1435938 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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2DDB - a bioinformatics solution for analysis of quantitative proteomics data.

Malmström Lars L   Marko-Varga György G   Westergren-Thorsson Gunilla G   Laurell Thomas T   Malmström Johan J  

BMC bioinformatics 20060320


<h4>Background</h4>We present 2DDB, a bioinformatics solution for storage, integration and analysis of quantitative proteomics data. As the data complexity and the rate with which it is produced increases in the proteomics field, the need for flexible analysis software increases.<h4>Results</h4>2DDB is based on a core data model describing fundamentals such as experiment description and identified proteins. The extended data models are built on top of the core data model to capture more specific  ...[more]

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