The Structure, Difficulties, and Successes of an Interdisciplinary Course to Introduce Biology, Computer Science, and Math Undergraduates to the Questions, Data, and Processes that Underlie Genome Analysis

Biology has entered the big data era, in which it is increasingly easier and cheaper to generate gigabytes of genomic data to answer a variety of biological questions. Thus, it is increasingly important for our undergraduate students to be able understand the various types of analyses that can be carried out using these genomic data. Furthermore, since these large datasets are made available online for other researchers to use, undergraduate students who have been introduced to the proper analysis tools can address novel biological questions using these datasets. Consequently, faculty members in the biology and computer science departments collaborated to put together the Genome Analysis course, which brings together students from math, computer science, and biology into a working arrangement that mirrors the work environments that exist today in both academia and industry. The students use their respective skills to collaborate to ask novel biological questions and to develop algorithms using R software to answer these questions. This novel interdisciplinary approach to the subject matter gives students a better working knowledge of the interrelated activities of the various professionals who must collaborate to answer genomic-level questions. The course serves as a model that faculty members at other universities could emulate as they attempt to include more genomics-level content in their curricula.