In a network orientation problem one is given a mixed graph, consisting of directed and undirected edges, and a set of sourcetarget vertex pairs. The goal is to orient the undirected edges so that a maximum number of pairs admit a directed path from the source to the target. This problem arises in the context of analyzing physical networks of protein-protein and protein- DNA interactions. While the latter are naturally directed from a transcription factor to a gene, the direction of signal flow in protein-protein interactions is often unknown or cannot even be measured en masse. One then tries to infer this information by using causality data on pairs of genes such that the perturbation of one gene changes the expression level of the other gene. In my talk I will discuss the complexity of the problem, show approximation algorithms for several variants of it and present an efficient ILP solution for it. I will then describe the application of this algorithm to orient protein-protein interactions in yeast, improving our understanding of the structure and function of the network.