Statistical Analysis of Biological Network Data

This paper discusses an area of application that seems somewhat remote from the other application areas of the symposia. The intension is not to dwell on biological and experimental issues, but briefly to introduce the biological background and setting and then move on to discuss aspects of statistical methodology that frequently are applied in the biosciences and elsewhere: Markov chain Monte Carlo (MCMC), likelihood-free inference and Bayesian Statistics. Whereas the MCMC has a long history in applied statistics, likelihood-free inference approaches are more recent, but have already found numerous applications in many areas of applied statistics; e.g. in econometrics.