Modeling Rho GTPase Dynamics Using Boolean Logic
Rho GTPases such as the canonical Rac1 and RhoA are embedded within complex networks requiring the precise spatiotemporal balance of GEFs, GAPs, upstream regulators, growth factors, and downstream effectors. A modeling approach based on Boolean logical networks is becoming an increasingly relied-upon tool to harness this complexity and elucidate further details regarding Rho GTPase signaling. In this methods chapter we describe how to initially create appropriately sized networks based on literature evidence; formalize these networks with reactions based on Boolean logical operators; implement the network into appropriate simulation software (CellNetAnalyzer); and finally perform simulations and make novel, testable predictions via in silico knockouts. Given this predictive power, the Boolean approach may ultimately help to highlight potential future avenues of experimental research.
Key wordsBoolean logic Mathematical modeling Networks RhoA
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