  To support and guide an extensive experimental research into systems biology
of signaling pathways, increasingly more mechanistic models are being developed
with hopes of gaining further insight into biological processes. In order to
analyse these models, computational and statistical techniques are needed to
estimate the unknown kinetic parameters. This chapter reviews methods from
frequentist and Bayesian statistics for estimation of parameters and for
choosing which model is best for modeling the underlying system. Approximate
Bayesian Computation (ABC) techniques are introduced and employed to explore
different hypothesis about the JAK-STAT signaling pathway.
