  Translating the complex, multi-dimensional data from simulations of
biomolecules to intuitive knowledge is a major challenge in computational
chemistry and biology. The so-called "free energy landscape" is amongst the
most fundamental concepts used by scientists to understand both static and
dynamic properties of biomolecular systems. In this paper we use Markov models
to design a strategy for mapping features of this landscape to sonic
parameters, for use in conjunction with visual display techniques such as
structural animations and free energy diagrams.
