Abstract
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 |
| Publisher | Elsevier |
| Pages | 65-91 |
| Number of pages | 27 |
| ISBN (Electronic) | 9780128012710 |
| ISBN (Print) | 9780128012130 |
| DOIs | |
| State | Published - Mar 25 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Mathematics
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