There are two people that I know of, doing research that resembles this. One is Francesco Stingo. He published a method for detecting binding between two different kinds of molecules--miRNA and mRNA. His method has a prior that is based in part on chemistry-based predictions of binding, and updated on the results of microarray experiments. The other is Cari Kaufman, who builds probability distributions over the results of a climate simulation. (the idea seems to be to extrapolate from simulations actually run with similar but not identical parameters)

Empirical priors + simulation of relevant models is somewhat similar to my idea on how to estimate P(causality|correlation): use explicit comparisons of correlational & randomized trials as priors when available, and simulate P(cauality|correlation) on random causal networks when not available.