Storing, linking, and mining microarray databases using SRS

Antoine Veldhoven¹ , Don de Lange¹ , Marcel Smid² , Victor de Jager³ , Jan A Kors⁴ and Guido Jenster¹

¹Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands

²Medical Oncology, Erasmus MC, Rotterdam, The Netherlands

³Bioinformatics, Erasmus MC, Rotterdam, The Netherlands

⁴Medical Informatics, Erasmus MC, Rotterdam, The Netherlands

author email corresponding author email

BMC Bioinformatics 2005, 6:192doi:10.1186/1471-2105-6-192


Published:	27 July 2005

Abstract

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.