An active area of research in pharmacology and drug discovery applies to functional selectivity: the ability of a ligand to selectively activate some signal transduction pathways as compared to the native ligand acting at the same receptor. At the theoretical level, biased signaling is supported by the concept of conformational selectivity: a given receptor may adopt several conformations, that can be stabilized by its interaction with a ligand, and each of these conformations potentially activates the downstream signaling pathways with different efficacies. At the practical level, experimentalists seek to quantify ligand bias in order to classify ligands according to their selectivity. One popular method uses the so-called operational model to fit dose-response curves. Our objective is then to design a method that fully take into account the kinetic nature of signaling pathways and as well as their possible cross-talks. I will explain how one can exploit kinetic data and dynamical reaction network modeling with suitable statistical framework to provide a complete “bias map” of a ligand, compared to the native ligand, that successfully answer to our objective. The methodology is illustrated with kinetic BRET measurements of effectors of the FSHR, stimulated by either the FSH or low molecular weight allosteric ligands.