Courses of Study 2022-2023 
    Dec 05, 2022  
Courses of Study 2022-2023

Computational Biology

In the Biological Sciences program .

In addition to the concentration requirements outlined below, all students must complete the Biological Sciences foundation requirements:

Computation has become essential to biological research. Technology for collecting high-throughput data, such as genomic technology, mass spectrometry, and MRI imaging, and the development of large-scale databases, such as those for genomes, epidemiology, and compilations of biological information types, have made available unprecedented amounts of detailed information that require computationally intensive methodologies to access and analyze. These data and computational methods are transforming almost all of biological research.

Problems investigated by computational biologists include topics as diverse as the genetics of disease susceptibility; comparing entire genomes to reveal the evolutionary history of life; predicting the structure, motions, and interactions of proteins; designing new therapeutic drugs; modeling the complex signaling mechanisms within cells; predicting how ecosystems will respond to climate change; and designing recovery plans for endangered species. The computational biologist must have skills in mathematics, statistics, machine learning, and the physical sciences as well as in biology. A key goal in training is to develop the ability to relate biological processes to computational models. Cornell faculty work primarily in six subareas of computational biology: 1. computational and statistical genomics, 2. population, comparative, and functional genomics, 3. bioinformatics, 4. proteomics, 5. ecology and evolutionary biology, and 6. statistical and computational methods for modeling biological systems.

Beyond core skills in mathematics, physical sciences and biology, the computational biology concentration requires additional coursework in mathematics and computer programming, a “bridging” course aimed at connecting biology to computation, and an advanced course where the theoretical/computational component of one aspect of biology is studied. Students should enroll in the more rigorous courses in the physical and mathematical sciences, and may wish to take additional courses in these areas.

Computational biology has applications as broad as biology itself. The problems of interest and the tools available to study them are constantly evolving, so students are encouraged to gain fundamental skills that will serve them throughout their careers. 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. This concentration is also an excellent preparation for graduate study in any area of biology or computational biology.

Students are required to select courses from the list below to complete the concentration; however, if students find another relevant course that is not listed, they may petition the Office of Undergraduate Biology.

Computational Biology Requirements:

  • All requirements must be taken for letter grade unless the course is offered S/U only. Exceptions to the grading option and any course substitutions must be approved via the biological sciences petition. Students are encouraged to discuss exceptions and course substitutions with their faculty advisor prior to submitting petition.
  • A grade of D- or better must be obtained to count course for concentration.
  • A minimum of 12 credits of concentration requirements


  • Many of the “bridging” and “advanced” courses listed above (items c and d) are offered only in alternate years or irregularly, and many have one or more prerequisites that are not required for the biological sciences major or this concentration. Students therefore need to plan well in advance how they will satisfy these requirements, and verify when course offerings will occur.
  • It is strongly recommended that students in this concentration use PHYS 2207 /PHYS 2208  to satisfy the core physics requirement.
  • It is strongly recommended that students complete the core organic chemistry requirement using the CHEM 1570  option, and that the time saved be used to take either CS 2110  or a second mathematics course from the list above.
  • One course may not be used to satisfy two different requirements simultaneously. For example, BTRY 3080  can be used to satisfy either requirement (b) or requirement (d), but not both.
  • Students who use BTRY 3080  to fulfill the additional mathematics requirement should not use ORIE 3500 - Engineering Probability and Statistics II  to fulfill the requirement for an advanced course.
  • AP credit in computer science can be used to satisfy part (a) One course in computer programming.

  • BIOG 49** courses (4990, independent study, TA, undergrad seminar) cannot be used towards the computational biology concentration.

Computational Biology Concentration Curriculum Learning Objectives

After completing the concentration in Computational Biology, students will be able to:

  • Have sufficient background knowledge in mathematics, probability, and statistics to be able to conceptualize key quantitative aspects of biological processes at the cellular, organismal or population level. 
  • Have the ability to apply computational and mathematical methods to model and/or analyze biological processes.
  • Have acquired working skills in at least one computer programming language to be able to implement modeling approaches.
  • Be able to organize, manipulate, and maintain the integrity of large, complex data sets.
  • Have developed advanced knowledge in at least one area of computational, statistical, mathematical, and/or quantitative modeling or analysis of data from biology.  This includes background knowledge of the current literature in the field, and ability to assess the merits of current literature.

Course Offerings in Computational Biology

A complete list of Biometry and Statistics courses