Slides from Computing for Graphical models (16 December 2011) — looks interesting:
Graphical models has expanded substantially over the past decade with the analysis of large data sets, in particular from bioinformatics and retail, with developments of inference in relation to causality, and with applications involving complex data structures. The ubiquitous nature of conditional independence has meant these models are applied in many different subjects. Computing for graphical models has always been difficult but recently user friendly open source software has become available. This meeting provided a platform to review the current provision and to elucidate remaining challenges in making graphical modelling more accessible to the wider scientific community.