Understanding how cellular signalling is flowing from the molecular to the cellular level is a key step to identify regulators of di↵erent diseases and revisit the development of new potential drug targets. For years, biological approaches of signalling did not allow to probe and control signalling at the sub-cellular level with enough accuracy in space and time to directly witness transfer of information in biological network. To analyze datasets where signaling is controlled spatio-temporally by optogenetic, we have developed a method which traverses the space of Random Walks with Restart (RWR) models, searching for the optimally biased walk in a given context. It will allow to integrate data of di↵erentially phosphorylated proteins obtained from longitudinal phospho-proteomics assay, in response to two di↵erent mode of optogenetic activation of the kinase Src, in order to reconstruct potential functional paths in the Protein-Protein interaction (PPI) network