Curtis Callan, Princeton University
Professor
Princeton, New Jersey
ccallan@Princeton.EDU
Office:
(609) 258-4321
Expert In
Bio/Research
For most of my career, I focused on understanding the workings of the quantum field theories that underlie the phenomena of particle physics. This led me to study issues in string theory (the construction of conformal field theories corresponding to solitons of various kinds) and in quantum gravi...
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Bio/Research
For most of my career, I focused on understanding the workings of the quantum field theories that underlie the phenomena of particle physics. This led me to study issues in string theory (the construction of conformal field theories corresponding to solitons of various kinds) and in quantum gravity (the problem of Hawking radiation and the endpoint of black hole evaporation). A side interest in the application of field theory techniques to condensed matter problems led to work on dissipative quantum mechanics and the (quantum) fracture of materials.
Over the past decade, however, my interest has shifted to theoretical problems in cellular biology. Modern biology increasingly has the ability to generate data (DNA sequence data, for one) in quantities that threaten to outrun our ability to comprehend it and use it for predictive purposes. I believe that the modeling and statistical inference approaches that are the stock in trade of physics are part of the answer to this growing problem, and I have been developing concrete examples of how this might work in problems ranging from gene regulation in bacteria to the functioning of the immune system in humans. In the process, I have become closely involved with the design and analysis of novel experiments, designed to answer unconventional, theoretically motivated, questions in biology.
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Over the past decade, however, my interest has shifted to theoretical problems in cellular biology. Modern biology increasingly has the ability to generate data (DNA sequence data, for one) in quantities that threaten to outrun our ability to comprehend it and use it for predictive purposes. I believe that the modeling and statistical inference approaches that are the stock in trade of physics are part of the answer to this growing problem, and I have been developing concrete examples of how this might work in problems ranging from gene regulation in bacteria to the functioning of the immune system in humans. In the process, I have become closely involved with the design and analysis of novel experiments, designed to answer unconventional, theoretically motivated, questions in biology.
Click to Shrink <<