In my area the most recent terribly-interesting paper was by the deCode people re: genetics of gene expression and inferring network 'modules' from patterns of

In my area the most recent terribly-interesting paper was by the deCode people re: genetics of gene expression and inferring network 'modules' from patterns of activity. There are more theoretically-interesting methods to deduce such graph-based causal networks (eg. Bayesian networks sampled via Metropolis-Hastings MCMC, or the paradoxically 'dumber' but more viable-in-the-cloud methods using MLEM, of which I am a proponent) but the deCode guys have the advantage of actually producing useful results right now. Overall (i.e. not restricted to my field of expertise) I would suggest that the biggest trove of ready-to-be-applied material on the Web is Andrew Moore's site at CMU: http://www.autonlab.org/tutorials/index.html http://www.autonlab.org/tutorials/index.html Possibly the worst-kept secret on the Web :-)