The tremendous increase in available biological information creates opportunities to decipher the structure, function and evolution of cellular components while presenting new computational challenges for performance and scalability. To fully utilize this large increase in knowledge, it must be organized for efficient retrieval and integrated for multi-dimensional analysis. Given this, biologists are able to invent new comparative sequence analysis protocols that will yield new and different structural and functional information.
Based on Microsoft SQL-server, we have designed and implemented the RNA Comparative Analysis Database -rCAD which supports comparative analysis of RNA sequence and structure, and unites, for the first time in a single environment, multiple dimensions of information necessary for alignment viewing, sequence metadata, structural annotations, structure prediction studies, structural statistics of different motifs, and phylogenetic analysis. This system provides a queryable environment that hosts efficient updates and rich analytics.
We will show how the performance and scalability of basic analysis tasks such as co-variation analysis can be improved using rCAD. We will also demonstrate the flexibility of using rCAD to form SQL solutions for innovative and complicated analysis problems