Growing amount of molecular biological data combined with current advances in modeling of complex systems provide unprecedented opportunities to understand biological evolution in a quantitative way. A quantitative description of an evolving system is the first step towards prediction and control, and it opens new exciting directions for highly interdisciplinary research. The central questions are: (i) to what degree we can predict the outcome of biological evolution, (ii) what features of the system are predictable and (iii) which features confer predictive value for a quantitative description of the system. This program brings together theoretical and experimental physicists, experimental biologists with an interest in quantitative modelling and mathematicians with interest in biological systems.
The conference will cover cutting-edge non-perturbative methods in quantum field theory, as well as mathematical aspects of integrability and its more traditional applications in condensed-matter physics and statistical mechanics.
Solvable models play a valuable a role in theoretical physics, as they illustrate general concepts in a simpler setting and provide insights into the qualitative features of more complex phenomena.