Making
sense of the ever-increasing amount and scope of biological
information--at levels of complexity ranging from individual molecules, through
molecular assemblies, to cells--requires sophisticated mathematical
and computational tools and concepts outside the realm of mainstream
biology. The graduate program in computational biology and molecular biophysics seeks to train a new generation of scientists to use these
tools and concepts to achieve a new level of understanding of biology.
The graduate program will be administered under the umbrella of the
BioMaPS Institute for Quantitative Biology, the goal of which is to
foster interdisciplinary research and education at the interface
between biology and the mathematical and physical sciences.
The institute faculty has been built on a critical mass of prominent
investigators in two major areas of interdisciplinary biomedicine:
structural biology and systems biology and bioinformatics. A major goal of the collaborative environment is to promote interaction between these areas.
The
graduate program's curriculum, course prerequisites, and admission
requirements have been designed to serve the needs of students with
diverse backgrounds, particularly those with quantitative training in
the physical, mathematical, and computer sciences. The program allows
the enrollment of interdisciplinary students who do not fit naturally
into any traditional graduate program but who show a strong interest
and aptitude for interdisciplinary biology research.
The curriculum
of the graduate program in computational biology and molecular biophysics involves three types of courses: background courses, core
courses, and electives.
Background Courses.
Students
with a limited background in an area of interdisciplinary biomedical
research may be required to take one or more specific undergraduate or
first-year graduate courses. In general, these requirements will be decided by the graduate program director or the associate director of graduate studies and the student's thesis adviser. The
specific options for students with a limited background in biology
and/or chemistry are outlined in the section "Requirements for the Ph.D. Degree."
Core Courses.
These
are specifically designed interdisciplinary courses that survey
particular areas of computational biology and molecular biophysics and
are meant to transition students into research at the forefront of the
field. These courses cover a broad range of topics, e.g., protein
structure; biophysics of molecular assemblies; algorithms in
bioinformatics; simulation techniques; biochemical and genetic
networks; signaling, data mining, and pattern recognition; mathematical
modeling and control theory.
Electives.
Courses
are taught by faculty members within traditional doctoral programs that
expose students to the techniques and scientific standards of
traditional disciplines, many of which form the basis of technical and
computational developments in computational biology and molecular
biophysics research. Students can select electives with the approval of
their advisory committee from virtually all graduate courses offered by
life science, mathematical and physical sciences, computer science, and
engineering programs at Rutgers, including biochemistry,
biomedical engineering, cell and developmental biology, chemical and
biochemical engineering, chemistry and chemical biology, computer
science, mathematics, mechanical and aerospace engineering, mechanics,
microbiology and molecular genetics, cellular and molecular
pharmacology, physics and astronomy, and statistics.
