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Survey of Biology for Computational Researchers course developed by IGERT trainees to teach cross-disciplinary peers the biology needed to engage in interdisciplinary research
Achievement/Results
The SCALE-IT IGERT has focused and been successful in training students from the biological domain sciences on the programming skills necessary to include high-performance computing options in biological research and to collaborate effectively with computer scientists on supercomputing projects. It has been more difficult to create the training elements that teach our computer science students what they need to know about biology to equally effective interdisciplinary researchers. That was the challenge undertaken this semester by three SCALE-IT trainees (Jordan Utley, Beth Johnson, and Denise Koessler). Under the guidance of Drs. Cynthia Peterson and Paul Armsworth, the students built a curriculum centered on computational biology research occurring on the UT campus.
The lessons were divided into six two-week modules; Genomics and Bioinformatics, Biochemistry and Biophysics, Cell Biology and Signaling, Immunology and Intercellular Communication, Phylogenetics and Evolution, and Population Ecology. The units began with a lecture/discussion format about key biological concepts related to the topic which led to a journal club and ended with an invited speaker. The course objectives were to overcome the biology/computer science lexicon barrier, bridge the culture gap between the disciplines, and create a vibrant community that facilitates collaborative research. The trainees were the course instructors and also developed an evaluation plan to measure the outcomes of the course and intent on publishing their results.
Address Goals
This course accomplishes a major educational objective for SCALE-IT’s mission to enable interdisciplinary computational research teams. A major barrier to effective incorporation of high-performance computing resources into biology research has been a limited ability of computer scientists to participate meaningfully in project design due to a limited understanding of the biological concepts. This hurdle must be overcome, and future innovations will require the active participation and insight of those most familiar with high-performance computing applications. After the first offering of this course, several meaningful interdisciplinary projects were proposed. These include an application of particle swarm theory to enable full parallelization of virtual docking algorithms and a strategy for using the nature of genetic regulatory algorithms that are applicable on many scales to map cellular communication networks in parallel. This class is a gateway educational experience that opens our interdisciplinary computational biology community up to a broader set of student backgrounds.
