We describe a novel approach for metabolic network reconstruction in order to switch from the full reaction-metabolite scheme to a more synthetic description at a pathway level. The network thus obtained retains much information of the original model, allowing easier graphical visualizations and multiscale modeling. We apply our approach to the state-of-the-art database of human metabolic network (Recon2): our approach allows different ranking of the network elements based on its topology and on Markov dynamics induced by network structure.