Often times, it is difficult to understand the role of a biomarker in a disease process. The signaling and biochemical networks within the cell are complex but when paired with other networks between cells and in a whole organism, the complexity goes up by significant dimensions.
To understand networks, there are various institutes using the network paradigm to understand stock markets social networks, and economic markets. Do the models developed with one of the networks help understand another network? Maybe not, though there are significant research dollars going into determining whether there is a crossover between internet networks and social networks or biological networks…. For example, understanding all the physical underpinnings of the neuronal pathways does not necessarily predict behavior. However, obvious breaks in networks might make the task easier to predict.
The one area that is fascinating is the internet. It is a complex network that is controlled by individual rules that helps derive the state but does it help predict any one server activity in a network? Probably not…
In a biological network, a drug that disrupts the network may change the function of the network but is it possible to predict the change? Scientists hope that a subtle change in the network may be determined by observing a few key characteristics (biomarkers). However, it would be a computationally interesting problem to predict biomarkers without necessary knowing all the nodes in the network or very specific characteristics. Unfortunately, the current state of knowledge is to disrupt the network and analyze everything. Then hope you find the key characteristic that represents the altered state of the network.