This workshop focuses on the complexity of dynamics and kinetics in complex systems, such as proteins, in terms of the underlying multidimensional energy landscape, the network structure in the conformational, or, in general, state space, and various mathematical models of nature. We aim at having an interdisciplinary meeting that brings both theoretical and experimental researchers together from different fields including time series analysis, energy landscape, statistical physics, network analysis, and single molecule experiments.

This year, the main questions to be addressed are:
1. What are the current and next generation experimental advances to probe the dynamics and kinetics of complex biophysical systems, such as single molecule spectroscopy and microscopy, cell imaging, multi-parameter measurements, and what are the desired analysis methods to scrutinize the observed data?

2. What are the appropriate mathematical languages to model complex dynamics and kinetics from experiments or computer simulations, such as generalized Langevin equations, master equations, networks, disconnectivity graphs? How can the mathematical models be constructed from scalar, multivariate or imaging (spatiotemporal) data? For example, how to extract hidden dimensions, how to reduce dimensions?

3. What are the dynamical and thermodynamical signatures of the constructed models? The related subjects are, for example, diffusion properties, memory effects, the quantification of multiple pathways on the energy landscape and its relations to the protein structures, equilibrium and nonequilibrium properties.

4. If the constructed models are complicated, e.g. in the conformational-space network, how can the essential features be extracted and represented, such as coarse-grained models, quantifying the large scale structure of networks, identifying reaction coordinates and flux?