Signal transduction allows a cell to communicate with its surroundings. Many diseases such as developmental disorders, autoimmunity, and cancer have been shown to arise from mutations of signal transduction pathway components. Gaining a comprehensive understanding of the cell's signaling mechanisms is vitally important as we attempt to control and combat these diseases. Boolean networks have recently emerged as a modeling tool that can successfully provide a qualitative description for signal transduction dynamics and reproduce complex behaviors such as excitation-adaptation, multistability, and hysteresis. A strength of the method is its ability to accommodate information gaps in the network topology, rules of interaction, initial conditions, and timing. Boolean models have led to a better understanding of cellular signaling and have provided predictions validated by follow-up experiments. The chapter presents an introduction to asynchronous Boolean models of signal transduction.
|Original language||English (US)|
|Title of host publication||Algebraic and Discrete Mathematical Methods for Modern Biology|
|Number of pages||27|
|State||Published - Mar 25 2015|
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