  The computer revolution has been driven by a sustained increase of
computational speed of approximately one order of magnitude (a factor of ten)
every five years since about 1950. In natural sciences this has led to a
continuous increase of the importance of computer simulations. Major enabling
techniques are Markov Chain Monte Carlo (MCMC) and Molecular Dynamics (MD)
simulations.
  This article deals with the MCMC approach. First basic simulation techniques,
as well as methods for their statistical analysis are reviewed. Afterwards the
focus is on generalized ensembles and biased updating, two advanced techniques,
which are of relevance for simulations of biomolecules, or are expected to
become relevant with that respect. In particular we consider the multicanonical
ensemble and the replica exchange method (also known as parallel tempering or
method of multiple Markov chains).
