Methods to Analyze Discrete Logical Models of Cell Signaling
When developing discrete logical models of cell signaling, the analysis of outcomes can be challenging. In this work, I am applying several analysis methods that are often used for studying biological models of other types (e.g., continuous, ODE models), but are not common for analysis of discrete logical models. Two of the methods I am using are Principal Components Analysis (PCA) and Boolean function sensitivity analysis. I am studying models of control circuitry of T cell differentiation and Malaria parasite infection in mosquito cells. PCA is used to compress a large amount of data obtained from simulation of these two models, while Boolean difference is applied to study sensitivity of Boolean functions in the models. The final goal of this work is to better uncover key regulatory components of these systems and predict how cells will respond to different stimuli.