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DIPSBC - data integration platform for systems biology collaborations

Authors :
Dreher Felix
Kreitler Thomas
Hardt Christopher
Kamburov Atanas
Yildirimman Reha
Schellander Karl
Lehrach Hans
Lange Bodo MH
Herwig Ralf
Source :
BMC Bioinformatics, Vol 13, Iss 1, p 85 (2012)
Publication Year :
2012
Publisher :
BMC, 2012.

Abstract

Abstract Background Modern biomedical research is often organized in collaborations involving labs worldwide. In particular in systems biology, complex molecular systems are analyzed that require the generation and interpretation of heterogeneous data for their explanation, for example ranging from gene expression studies and mass spectrometry measurements to experimental techniques for detecting molecular interactions and functional assays. XML has become the most prominent format for representing and exchanging these data. However, besides the development of standards there is still a fundamental lack of data integration systems that are able to utilize these exchange formats, organize the data in an integrative way and link it with applications for data interpretation and analysis. Results We have developed DIPSBC, an interactive data integration platform supporting collaborative research projects, based on Foswiki, Solr/Lucene, and specific helper applications. We describe the main features of the implementation and highlight the performance of the system with several use cases. All components of the system are platform independent and open-source developments and thus can be easily adopted by researchers. An exemplary installation of the platform which also provides several helper applications and detailed instructions for system usage and setup is available at http://dipsbc.molgen.mpg.de. Conclusions DIPSBC is a data integration platform for medium-scale collaboration projects that has been tested already within several research collaborations. Because of its modular design and the incorporation of XML data formats it is highly flexible and easy to use.

Details

Language :
English
ISSN :
14712105
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.984fa01812be448789d8190edfc0254f
Document Type :
article
Full Text :
https://doi.org/10.1186/1471-2105-13-85