Departmental Groups
Related Research Groups
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Biophysics Theory and Experiment
Almost every area of modern biology, from molecular genetics to
neuroscience, is being revolutionized by large scale,
quantitative experiments. At the same time, developments in statistical
mechanics and dynamical systems have prepared the physics community to address
theoretical questions posed by more complex systems. From
observing the dynamics of single biological molecules to building theories for
the neural networks that make possible our perception of the world,
there are myriad challenges for physicists and biologists willing to
explore the boundary between their disciplines. We believe that the
opportunities extend far beyond the application of known physical
principles and experimental techniques to biological systems:
biology offers us examples of very special physical systems, in which the
state of the system represents information that has meaning to the
organism and the dynamics of the system implements an "algorithm for
living" that embodies functions essential for survival in a complex,
fluctuating environment. We would like to make precise these intuitive
notions of meaning and functionality. Our work is animated by the belief
that, as in other areas of physics, the striking qualitative phenomena of
life should have correspondingly deep theoretical explanations, and
that this understanding ultimately will be tested only by a new generation
of quantitative experiments.
Princeton University offers a unique environment for research and
education at the interface between physics and biology. The
Department of Physics has several faculty members with interests in biology,
the Department of Molecular Biology has several faculty members who
were educated as physicists, and many traditional biology laboratories
on campus have students or postdocs with physics backgrounds.
Barriers between departments are low, and reduced still further by
multidisciplinary initiatives such as the
Lewis-Sigler Institute, the
Neuroscience graduate program, and the
Biophysics certificate program for undergraduates.
In just the past few years, the number of
Princeton faculty with interests at the physics/biology interface has grown
enormously, creating new opportunities for graduate students and
postdoctoral fellows.
| Robert H. Austin: What physics can do for biology, what biology can do
for physics. Dynamics of proteins, DNA and cells |
William Bialek: Coding, computation and learning in the nervous system; noise and the physical limits to biological functions; statistical mechanics and information theory |
| Curtis G. Callan: Theoretical problems in genomics |
Michael Desai: Population
genetics, evolutionary theory, and experimental evolution. |
| Matthias Kaschube: Collective behavior and emergent phenomena in biological systems; function and development of the nervous system; design principles in the visual cortex |
William Ryu: Experimental biophysics, C. Elegans behavior |
| Eva-Maria Schoetz:
Biophysics of development and regeneration. |
Joshua Shaevitz: How do bacteria
acquire their specific shapes and structural properties? How do cells
transport and organize their contents? Dynamic force measurements of
proteins and living cells.
(Arriving July 2007) |
| David Tank: measurement and analysis of electrochemical signaling in the nervous system; neural integrators and short term memory; role of feedback in neural circuit dynamics. |
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IN THE BIOLOGY DEPARTMENTS: |
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Michael J. Berry Information, efficiency, and adaptation in the neural
code of the retina; statistical structure of natural scenes; eye
movements and visual behavior |
Edward Cox The genesis of large scale spatial patterns in
self-organizing biological systems |
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John Hopfield Statistical dynamics in biology:
Algorithms, biophysics, and 'hardware' in neurobiological computation |
Saeed Tavazoie Studies of connectivity, dynamics, and evolution in biological networks through whole-genome and computational approaches |
Samuel Wang
Neurobiology:
(1) optical approaches to understandinglearning rules in single synapses, and
(2) theoretical approaches to understanding scaling relationships in brain anatomy |
Ned Wingreen
Modeling intracellular networks in bacteria: chemotaxis, quorum sensing, cell division, metabolism, circadian rhythms.
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Leonid Kruglyak
Experimental, theoretical and computational approaches using genome- scale data to understand how variation in DNA sequence is created by evolutionary forces and how this variation leads to all the observable differences among individuals within a species. |
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