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Databases and software are important to manage modern high-throughput laboratories and store clinical and genomic information for quality assurance. Commercial software is expensive, with proprietary code issues, while academic versions have adaptation issues. Our aim was to develop an adaptable in-house software system that can store specimen- and disease-associated genetic information in biobanks to facilitate translational research. A prototype was designed per the research requirements, and computational tools were used to develop the software under three tiers, using Visual Basic and ASP.net for the presentation tier, SQL Server for the data tier, and Ajax and JavaScript for the business tier. We retrieved specimens from the biobank using this software and performed microarray-based transcriptomic analysis to detect differentially expressed genes (DEGs) ... (Full article...)
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