Life is a mess.

Biological phenomena cuts spatial and temporal scales in a startling way, involving organisms that are greatly different at the structural, functional, and taxonomic level. Biology is, in a way, the very definition of complexity.

Amid this jumble, though, a striking connection with the world of the physical and mathematical sciences, sometimes emerges, calling for a quantitative description of biological systems able to extend to biology the great predictive power of physics. In doing so, physical biology challenges the physicist with new problems, which in turns expand considerably the very boundaries of physics itself.

To pursue this idea, though, the great diversity of biology needs to be tamed and transcended to a certain extent. Physics is optimally suited for this task. The success of all great physical theories is often based upon a profound conceptual pillar: not always one needs to describe all microscopic details making up a complex system, as simplified effective theories, in which only the most relevant variables are included, are often able to capture the quantitative essence of the physical problem at hand, no matter how complicated it was.

Biological systems have no less details than physical ones; in fact, modern biology is a celebration of the remarkable diversity of life. New
experimental techniques have uncovered unimagined themes and variations in the biological mechanisms on every scale. Yet physical biology is more than data mining. Is it possible to extract from this mass of data unifying general principles that engage with the complexity of biology?
Can we use statistical mechanics, stochastic processes, nonlinear dynamics, field theory, and the whole great toolbox of modern physics, to formulate predictive theories of biological systems?

These are the questions that people working at ISC in the Physical Biology sector are engaged with.

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