In the recent years, biology has been shifting its focus from studies
of molecular components of organisms to attempting to understand
entire biological systems as a whole. This has opened up new
opportunities for the physical way of thinking in biology, and it
allowed us to wonder if there exists a biological systems theory as
general as, say, the Landau theory in physics, and thus capable of
"explaining" many diverse biological implementations of the same
physical phenomenon at once. In this talk, I will describe a very
small corner of systems biophysics, where the first steps towards a
general understanding may have already been made. Here, using the
tools of information theory and statistical physics, we have been able
to make small steps towards formulation of and answers to questions
like: What are the signal processing capabilities of biological
networks? Which functions can they perform? How important is
stochasticity? How can we understand network macroscopic dynamics
without microscopic data? How can the networks be coarse-grained?
Interestingly, very similar questions and tools can be used in the
domain of cellular regulatory networks and systems neuroscience, and
the talk will emphasize the similarity. While addressing these
questions, I will show examples of cross-fertilization between physics
and systems biology: on the one hand, physics will suggest tools for
faster simulation and deeper understanding of biochemical networks
dynamics, and, on the other, study of a biological problem will show
an unexpected and illuminating connection between seemingly unrelated
areas of theoretical physics.