Therefore, we need new systems biology tools that can quantify the role of individual or multiple genes in disease development. The recently developed fault diagnosis engineering technology for molecular networks is a promising tool that has such capabilities and can model complex trait disorders such as schizophrenia. The double fault model presented in this study can be extended to a multi-fault model, in which simultaneous dysfunction of several genes involved in schizophrenia could be studied. The presented fault diagnosis approach can model a complex trait disorder such as schizophrenia because it can quantify the role of each individual gene, pairs of genes, as well as the combination of multiple genes known to be involved in the pathogenesis of this complex trait disorder. In the previous fault analysis paper we studied the case where each molecule had an active or inactive state. Here we have expanded the approach by considering three levels of activity for each molecule, and have developed a method for calculating network vulnerabilities for the ternary model. Our results for the caspase network show that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. Our results suggest that for the purpose of fault diagnosis it is more practical to start with the less complex active/inactive fault diagnosis approach, to analyze the malfunction of signaling networks. This assists in identifying many molecules whose dysfunction do not contribute to the network failure. Afterwards, if one may want to further study the role of molecules with GDC-0449 Hedgehog inhibitor medium or high vulnerabilities, he can focus on building a less complex model where only the small set of such molecules have three activity levels. Overall, the important conclusion is that by increasing the number of activity levels for each molecule, the complexity of the model and its fault analysis significantly increases. However, the predictive power of the model does not necessarily appear to increase proportionally. There have been some recent studies on tristability in genetic networks : It is shown that the microRNA-transcription factor self-activating chimera toggle switches can exhibit three metastable states, whereas the microRNA/ZEB ternary switch is shown to result in three phenotypes. Our ternary network analysis, however, is different from these studies. We have focused on signaling networks with ligands as inputs and some molecules as outputs, and have considered three activity levels for each molecule. Our goal is to determine the vulnerability of the network to the possible dysfunction of its molecular components. This research goal is different from those considered in and, and the methodology developed here addresses a different problem. Periodontitis is a chronic infectious disease that can lead to the destruction of periodontal tissues and even tooth loss. Therapeutic strategies for the treatment of periodontitis include not only the control of local inflammation.