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Relational Databases: A Transparent Framework for Encouraging Biology Students To Think Informatically

Michael Rice^*, William Gladstone^*,, and Michael Weir^,

^* Department of Mathematics and Computer Science and Department of Biology, Wesleyan University, Middletown, CT 06459

Corresponding author. E-mail address: mweir{at}wesleyan.edu.

We discuss how relational databases constitute an ideal framework for representing and analyzing large-scale genomic data sets in biology. As a case study, we describe a Drosophila splice-site database that we recently developed at Wesleyan University for use in research and teaching. The database stores data about splice sites computed by a custom algorithm using Drosophila cDNA transcripts and genomic DNA and supports a set of procedures for analyzing splice-site sequence space. A generic Web interface permits the execution of the procedures with a variety of parameter settings and also supports custom structured query language queries. Moreover, new analytical procedures can be added by updating special metatables in the database without altering the Web interface. The database provides a powerful setting for students to develop informatic thinking skills.

Key Words: relational database • Drosophila splice sites • information content • undergraduate • bioinformatics