Evaluating ligand-receptor networks of TGF-beta with membrane computing

Ligand-Receptor Networks of TGF-beta plays essential role in transmitting a wide range of extracellular signals that affect many cellular processes such as cell growth. However, the modeling of these networks with conventional approach such as ordinary differential equations has not taken into account, the spatial structure and stochastic behavior of processes involve in these networks. Membrane computing as the alternatives approach provides spatial structure for molecular computation in which processes are evaluated in a non-deterministic and maximally parallel way. This study is carried out to evaluate the membrane computing model of Ligand-Receptor Networks of TGF-beta with model checking approach. The results show that membrane computing model has sustained the behaviors and properties of Ligand-Receptor Networks of TGF-beta. This reinforce that membrane computing is capable in analyzing processes and behaviors in hierarchical structure of cell such as Ligand-Receptor Networks of TGF-beta better than the deterministic approach of conventional mathematical models.