Computation has become essential to biological research. Genomic databases, protein databanks, MRI images of the human brain, and remote sensing data on landscapes contain unprecedented amounts of detailed information that are transforming almost all of biology. The computational biologist must have skills in mathematics and computation as well as in biology. A key goal in training is to develop the ability to relate biological processes to computational models.
The field provides interdisciplinary training and research opportunities in a range of subareas of computational biology involving topics such as DNA and protein databases, protein structure and function, computational neuroscience, biomechanics, population genetics, and management of natural and agricultural systems.
Students majoring in computational biology are expected to obtain a broad, interdisciplinary knowledge of fundamental principles in biology, computational science, and mathematics. But because the field covers a wide range of areas, it would be unrealistic to expect a student to master each facet in detail. Instead, students choose from specific subareas of study: they are expected to develop competence in at least one specific subdomain of biology (i.e., genetics, macromolecular biology, cellular biology, organismal biology, behavioral biology or ecology) and in relevant subareas of computational science and mathematics.
Students are supervised by field faculty drawn from sixteen departments.
Subject and Degrees
- Computational Biology (Ph.D.) (Ithaca)
Concentrations by Subject
- computational behavioral biology
- computational biology
- computational cell biology
- computational ecology
- computational genetics
- computational macromolecular biology
- computational organismal biology