The Ph.D. in Computational Biology is intended for students who are interested in advancing studies at the interface of biological sciences and computer science. The program is designed to allow rigorous pursuit of both disciplines for the purpose of advancement of research that lies directly at the interface. The Cornell program has a strong emphasis on interdisciplinary research that bridges the gap between diverse biological disciplines, from behavior and ecology to molecular biology, to computational fields including algorithm development, numerical analysis and computationally intensive statistics. The focus is on advancement of fundamental research through recognition of common needs and goals of researchers and students working on computationally intensive aspects of biological research.
The program allows for specialization within the biological and computational sciences. The biological subareas are organized by biological size scale: Genetic, Macromolecular, Cellular, Organismal, Behavioral, and Ecological biology. Expertise within one of these is required. The computational subareas are Mathematical science, Computational science, and Programming. Distributed expertise in all three areas is required.
A student who is awarded a Ph.D. in Computational Biology will need to achieve three objectives: (a) demonstrated competence in the disciplines that contribute to the field, (b) depth in at least one computational and one biological aspect of the field, (c) original research, on a topic from one or more of the Computational Biology concentrations.
Entering students may have a diversity of backgrounds. There will be undergraduates who have already directly worked in both biological and computer sciences, either as biologists who learned and applied a computer language in undergraduate research projects, or as a computer science student who worked on a biological application. But many entering students will not have a balanced background, and instead will have much more experience in either the biological or the computational side. The field will be looking for highly able students who can demonstrate strong potential in both computer science and the biological sciences.
The program requires depth in the form of strong analytical skills, and breadth in an appreciation and understanding of a number of the focus areas. An ideal entering student will have an undergraduate degree in a related area, with solid writing skills, computing experience, and a mathematical foundation that includes probability, statistics, and linear algebra. However, the program is designed so that students have an opportunity to fill gaps in their background at the beginning of their studies. In practice we expect that most entering students will have a strong undergraduate degree, with a major in a relevant field, including a significant quantitative or technical component.
Students leaving the program will have a very strong knowledge of the intersection between computational and biological sciences. There is great demand for students with such "bridging"? skills. As such they will be very well placed to follow professional careers in both academic and the biotech industry.
Academic Requirements
Students must demonstrate competency within both the Biological and Computational foci as described below.
Academic Requirements
Within the biological focus area, students must demonstrate competency within one subarea by completing four course-equivalents (see below) for the subarea. Additional breadth is suggested; at the discretion of the Special Committee, one of the four required courses may be assigned in a second area.
| Genetic | (e.g., genomics, population genetics) |
| Macromolecular | (e.g., protein structure prediction, proteomics, protein dynamics, DNA and RNA structure) |
| Cellular | (e.g., expression level analysis, signal pathway modeling) |
| Organismal | (e.g., modeling hand and heart motion, sensory systems) |
| Behavioral | (e.g., animal behavioral modeling) |
| Ecological | (e.g., population and ecosystem modeling) |
Competency within each subarea is defined by the Special Committee witin the guidelines provided by the Field Executive Committee. One guideline is that the requirement for a student with no background in the area will consist of 4 (3-credit) courses plus additional background material learned by self-instruction (e.g., organic chemistry). Students with extensive background in a subarea may "advance place" some requirements based on prior course grades and diagnostic oral examination.
Computational focus
Students must demonstrate competency within each of three areas (see below). Programming competency will usually be satisfied by small projects submitted to the Special Committee. Mathematical and computational competency will be demonstrated by completing a total of four course-equivalents (see below). The courses will be selected in consultation with the Special Committee from the course list to provide the appropriate foundation for the student's anticipated area of study. At least two course-equivalents will be in Mathematical Science and at least one in Computational Science.
| Mathematical science | i.e., applied mathematics and statistics (differential equations, linear algebra, analysis, discrete mathematics, engineering mathematics, statistics) |
| Computational science | e.g., databases, numerical analysis, algorithm |
| Programming | Standard metalanguage (e.g., Matlab, Mathematica, Stat package) (required), Basic language programming skills (e.g., C++) (required) |
Course Equivalents
Students may "place" course-equivalents based on prior study. It is expected that a typical student will place 2-3 of the course requirements. At least three of the courses actually taken during the program must be at the graduate level. Placement recommendations will be made following an informal oral examination administered by the Placement Committe as soon as possible after the student enters the field. These recommendations will be added to the student's folder as a guideline for the Special Committee. The Special Committee will ultimately make the final assessment.
Survey course
In addition to the course requirements above, it is anticipated that students will take a survey course that will be developed in the future (i.e., once there are enough students in the program).
Minor
A single minor is required. In consultation with the DGS, students should select this during their first year. The minor will usually be a related biological, computational, mathematical, or physical science field.
Special committee
Students should assemble a Special Committee at the end of the first year. This will consist of the thesis research supervisor (the Chairperson of the Special Committee), a faculty member representing the minor subject, and another faculty member from the field of Computational Biology. The student chooses the members other than the Chairperson with approval by the Director of Graduate Studies. The DGS will serve as Chairperson until the Special Committee has been chosen.
A-exam
The A-exam will be administered by the Special Committee and will consist of: (1) an oral examination to assess completion of the competency requirements in the Biological and Computational foci and in the proposed area of research. (2) a short (e.g., 10 page) written presentation outlining the background, progress and plans for thesis research (submitted to the committee at least 1 week prior to the exam), and (3) a short (1/2 hour) oral presentation of research progress and thesis research plans. The A-exam should be taken before the start of the third year.
Masters degree
The field will only accept students for a Ph.D. program. At the discretion of the Special Committee, students who are not making satisfactory performance may be awarded a terminal Masters degree if they have satisfactorily completed the competency requirements. Students who pass the A-exam may be awarded a Special Masters.
Ph.D. Thesis
Students are expected to make a thesis proposal by the end of their third year as a part of the A-exam. As part of the thesis proposal, the student will be required to demonstrate depth in at least one concentration, sufficient to carry out fundamental research. The student's Ph.D. committee will decide how this expertise will be evaluated. The "Papers Option" is acceptable.
In addition to the required group of 600-level courses, the student's committee may require additional courses before approving the thesis proposal. Each student must satisfy the requirements of one Minor in another graduate field. Primary subject areas of a Ph.D. thesis in Computational Biology include: computational genetics, computational macromolecular biology, computational cell biology, computational organismal biology, computational behavioral biology, and computational ecology.
Requirements for Computational Biology Minor
Students must complete the academic requirements of the field. It is expected that a typical student will take four of the courses from study associated with their major.