  Theoretical physicists have been fascinated by the phenomena of life for more
than a century. As we engage with more realistic descriptions of living
systems, however, things get complicated. After reviewing different reactions
to this complexity, I explore the optimization of information flow as a
potentially general theoretical principle. The primary example is a genetic
network guiding development of the fly embryo, but each idea also is
illustrated by examples from neural systems. In each case, optimization makes
detailed, largely parameter-free predictions that connect quantitatively with
experiment
