Communication between cells and their microenvironment is critical for physiological processes such as development, immune response and wound healing. Perturbations in the processing of information leads to many diseases including fibrosis and cancer. The complexity of communication arises from the spatial and dynamic arrangements of a variety of molecules along with their interactions. While such complexity benefits to the plasticity of cell responses, at the opposite it limits the efficiency of therapeutic targeting.
New therapeutic approaches requires the understanding of such complex networks that are nonlinear, time-, and/or space-dependent. Based on mathematical models and computational methods, systems biology helps biologists understand the interactions between components of a biological system and how these interactions give rise to the function and behavior of that system. In collaboration with the Institut de Recherche en Informatique et Systèmes Aléatoires (https://www.irisa.fr/en) our group developed computational approaches for modeling signaling networks asociated with the profibrogenic growth factor TGF-β and we proposed a new formalism CADBIOM to investigate signaling trajectories (http://cadbiom.genouest.org/index.html).