From statistical mechanics to information theory: understanding biophysical information-processing systems
arXiv:1006.4291
Abstract
These are notes for a set of 7 two-hour lectures given at the 2010 Summer School on Quantitative Evolutionary and Comparative Genomics at OIST, Okinawa, Japan. The emphasis is on understanding how biological systems process information. We take a physicist's approach of looking for simple phenomenological descriptions that can address the questions of biological function without necessarily modeling all (mostly unknown) microscopic details; the example that is developed throughout the notes is transcriptional regulation in genetic regulatory networks. We present tools from information theory and statistical physics that can be used to analyze noisy nonlinear biological networks, and build generative and predictive models of regulatory processes.
Lecture notes for 2010 Summer School on Quantitative Evolutionary and Comparative Genomics, Okinawa Institute of Science and Technology; 52 pages
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