Relational databases: a transparent framework for encouraging biology students to think informatically.
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.
Rice
Michael
M
Department of Mathematics and Computer Science, Wesleyan University, Middletown, CT 06459, USA.
Gladstone
William
W
Weir
Michael
M
D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000193:education*; D030541:Databases, Genetic; D004330:Drosophila / Q000235:genetics; D023281:Genomics / Q000193:education*; D020407:Internet; D007858:Learning / Q000502:physiology*; D018794:Problem-Based Learning / Q000379:methods; D015397:Program Evaluation; D022821:RNA Splice Sites / Q000235:genetics; D012984:Software; D013334:Students / Q000523:psychology*; D011795:Surveys and Questionnaires; D013663:Teaching / Q000379:methods*; D013664:Teaching Materials
D022821:RNA Splice Sites