  Molecular simulations and biophysical experiments can be used to provide
independent and complementary insights into the molecular origin of biological
processes. A particularly useful strategy is to use molecular simulations as a
modelling tool to interpret experimental measurements, and to use experimental
data to refine our biophysical models. Thus, explicit integration and synergy
between molecular simulations and experiments is fundamental for furthering our
understanding of biological processes. This is especially true in the case
where discrepancies between measured and simulated observables emerge. In this
chapter, we provide an overview of some of the core ideas behind methods that
were developed to improve the consistency between experimental information and
numerical predictions. We distinguish between situations where experiments are
used to refine our understanding and models of specific systems, and situations
where experiments are used more generally to refine transferable models. We
discuss different philosophies and attempt to unify them in a single framework.
Until now, such integration between experiments and simulations have mostly
been applied to equilibrium data, and we discuss more recent developments aimed
to analyse time-dependent or time-resolved data.
