Computational Biology Program
Biology Track
Biology Track
What is Computational Biology?
The Computational Biology Degree (Biology Track) is for the student who has an interest in Applied Biological Computation, with an emphasis on solving biological problems. Biological research in the 21st century will require scientists to be trained in the analysis and interpretation of large, complex sets of high throughput data. It is predicted that most laboratories in biological and biomedical disciplines will need individuals trained in Computation to analyze large datasets and liaison with big data centers. These disciplines include (but are not limited to) genomics, systems biology, imaging, proteomics, metabolomics, ecology and phylogeny. Students in this program will complete a core curriculum of Math, Computer Science, Scientific Computing, Chemistry, Statistics and Biology courses. In the Biology track, students will choose a sub-discipline and seek out a mentor who will serve as their internship mentor and advise them as to the elective courses most appropriate to that sub-discipline and guide them in career options.
What distinguishes Computational Biology from Computational Science majors?
A degree in Computational Biology differs from a Degree in Computational Science (focusing on biological computing) in that the Computational Science degree is rigorously math and theory oriented, emphasizing development of new computational approaches, while the Computational Biology degree will emphasize applications of existing tools to analyze large biological datasets.
What distinguishes Computational Biology (Biology Track) from Computational Biology (Computer Science Track)?
The emphasis of the biology track is in immersion of students in a biological problem. Students have fewer didactic requirements but are required to perform a Research Practicum that will immerse them in a biological laboratory setting and provide opportunities to co-author publications. The emphasis of the computer science track is on familiarity with computer science which can be applied in many computational settings and does not require a research experience (although students may elect to have such an experience).
