Software
Storing, linking, and mining microarray databases using SRS
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* Corresponding author: Guido Jenster g.jenster@erasmusmc.nl
1 Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands
2 Medical Oncology, Erasmus MC, Rotterdam, The Netherlands
3 Bioinformatics, Erasmus MC, Rotterdam, The Netherlands
4 Medical Informatics, Erasmus MC, Rotterdam, The Netherlands
BMC Bioinformatics 2005, 6:192 doi:10.1186/1471-2105-6-192
Published: 27 July 2005Abstract
Background
SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray data to facilitate the analyses of biological questions and non-hypothesis driven quests. Here we report various solutions and tools for integrating and mining annotated expression data in SRS.
Results
We devised an Auto-Upload Tool by which microarray data can be automatically imported into SRS. The dataset can be linked to other databases and user access can be set. The linkage comprehensiveness of microarray platforms to other platforms and biological databases was examined in a network of scientific databases. The stored microarray data can also be made accessible to external programs for further processing. For example, we built an interface to a program called Venn Mapper, which collects its microarray data from SRS, processes the data by creating Venn diagrams, and saves the data for interpretation.
Conclusion
SRS is a useful database system to store, link and query various scientific datasets, including microarray data. The user-friendly Auto-Upload Tool makes SRS accessible to biologists for linking and mining user-owned databases.