Information theory for data analysis in biology

One of the key outputs of Shannon's information theory is that it gave as a framework for quantifying dependence, which is in turn crucial for a robust identification actual mechanisms in the chaos of reality.
On the other hand, it shifted many practical issues of modelling into the estimation realm, especially when higher order reasoning is required. 
In my talk, I will present a novel approach into estimating information measures tailored toward typical biological data, as well as some current work devoted to network inference.