The emerging field of computational and systems biology represents an integration of concepts and ideas from the biological sciences, engineering disciplines, and computer science. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created a new opportunity to focus on understanding biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are relatively new to biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, math and computer science. Graduates of the program will be uniquely prepared to develop new methods, make novel discoveries and establish new paradigms. They will also be well-positioned to assume critical leadership roles in both academia and industry, where this new area is becoming increasingly important.
At MIT, research and education in Computational and Systems Biology are characterized by "the four M's"—measurement, mining, modeling, and manipulation, with many diverse research groups working in these complementary areas. Efforts in measurement emphasize the systematic collection of data and the development of new experimental methods (e.g., using microfabrication). Research in mining and modeling aims to develop and apply algorithms to identify underlying relationships in large datasets, and to capture these in predictive models. Finally, design is an important facet of systems biology where the goal is to make rational modifications to biological systems. This type of manipulation provides a test of understanding and promises a route to practical advances in biotechnology and medicine. The strong focus on building detailed, quantitative, and predictive models of biological systems is a defining feature of the MIT program. Such models form the basis of understanding and the foundation of design.
More than 90 faculty members at MIT participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering. Thus, students in the CSB graduate program can pursue thesis research in a wide variety of different laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision from faculty members with different areas of expertise. Areas of active research include computational biology and bioinformatics, gene and protein networks, molecular biophysics, instrumentation engineering, cell and tissue engineering, predictive toxicology and metabolic engineering, imaging and image informatics, nanobiology and microsystems, biological design and synthetic biology, neurosystems biology, and cancer biology.
The CSB PhD program is an Institute-wide program that has been jointly developed by the Department of Biology, the Department of Electrical Engineering and Computer Science, and the Department of Biological Engineering. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants are required to have an undergraduate degree, preferably with dual emphasis in biology (or a related field) and also in computer science, math, physics or an engineering discipline.
All students pursue a core curriculum that includes classes in biology and computational biology, along with a literature-based class in computational and systems biology. Advanced electives in science and engineering enhance both the breadth and depth of each graduate's education. During their first year, in addition to coursework, students carry out rotations in research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to do their thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research, because multidisciplinary research spans different academic cultures and modes of operation. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.
The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that are selected by each student in close consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, but at the same time to provide oversight and guidance to ensure that they receive rigorous and thorough training.
The core curriculum consists of three classroom subjects plus a set of four two-month rotations in different research groups. The classroom subjects fall into three areas described below.
Modern Biology (One Subject): A term of modern biology at MIT strengthens the biology base of all students in the program. Subjects in cell biology, molecular biology, neurobiology, biochemistry, or genetics fulfill this requirement. The particular course taken by each student will depend on their background and will be determined in consultation with graduate committee members.
Computational Biology (One Subject): A term of computational biology provides students with a background in the application of computation to biology, including analysis and modeling of sequence, structural, and systems data. This requirement can be fulfilled with "Foundations of Computational and Systems Biology."
Topics in Computational and Systems Biology (One Subject): All first-year students in the program participate in "Topics in Computational and Systems Biology," a literature-based exploration of current frontiers and paradigms in this emerging field. This subject is limited to students in the CSB PhD program in order to build a strong community among the class. It is the only subject in the program with such a limitation.
Research Group Rotations (Four Rotations): To assist students with lab selection and provide a range of research activities in computational and systems biology, students participate in four two-month long research rotations during their first year. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.
The requirement of four advanced electives is designed to develop both breadth and depth for students in the CSB PhD program. The electives add to the base of the diversified core and contribute strength in areas related to student interest and research direction. To develop depth, two of the four advanced electives must be in the same area (department). To develop breadth, at least one of the electives must be from an engineering discipline and at least one from a biology-related field. Each student will design a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.
Additional Subjects: As is typical for students in other doctoral programs at MIT, CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics considered for the thesis research in later years. The CSB Graduate Committee will work with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.
Qualifying Exams: In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination in the second year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.
Bruce Tidor, PhD
Professor of Biological Engineering and Computer Science
Chris Burge
Associate Professor of Biology
Chair of the Committee
Drew Endy, PhD
Assistant Professor of Biological Engineering
Alan D. Grossman, PhD
Praecis Professor of Biology
Amy E. Keating, PhD
Robert Swanson Career Development Assistant Professor of Biology
Scott R. Manalis, PhD
Associate Professor of Biological and Mechanical Engineering
Joel Voldman, PhD
Assistant Professor of Electrical Engineering
Forest White, PhD
Assistant Professor of Biological Engineering
Jacob K. White, PhD
Professor of Electrical Engineering