Sorry for the drive-by comment, but the remark

> In Bayesian networks the edges indicate causality, some random variable affecting another. That’s a seemingly different use of edges from reaction networks, where they mean something turning into something else! So we’ll need to invent a sufficiently rich framework to fit these two together.

reminded me of what I did while deriving the [discrete master equation](http://phorgyphynance.wordpress.com/2011/10/29/network-theory-and-discrete-calculus-the-discrete-master-equation/).

> In Bayesian networks the edges indicate causality, some random variable affecting another. That’s a seemingly different use of edges from reaction networks, where they mean something turning into something else! So we’ll need to invent a sufficiently rich framework to fit these two together.

reminded me of what I did while deriving the [discrete master equation](http://phorgyphynance.wordpress.com/2011/10/29/network-theory-and-discrete-calculus-the-discrete-master-equation/).