The computational biologist must have skills in mathematics, statistics and the physical sciences as well as in biology. A key goal in training is to develop the ability to relate biological processes to mathematical models that can be solved computationally. These include the computational study of topics such as DNA databases, protein structure and function, computational neuroscience, biomechanics, population genetics, and management of natural and agricultural systems. Students should enroll in the more rigorous courses in the physical sciences and be well prepared in mathematics. Depending on student interest, students may wish to pursue additional courses in these areas.
Computational biology is a new emerging area that has applications as broad as biology itself.
The program is an excellent preparation for students who wish to specialize in one of these computational areas in graduate school. There is great, and increasing, demand for research scientists and technical personnel who can bring mathematical and computational skills to the study of biological problems.