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Abbreviations
- Connectivity matrix:
-
In a Boolean network model, the information about who is interacting with whom is stored in the connectivity matrix. This static wiring diagram can be described by parameters from graph theory, such as the degree distributions of its elements or nodes.
- Activity, sensitivity :
-
Boolean functions define how elements of a network interact. Activity and sensitivity are parameters describing the dynamic properties of single network elements or nodes. The activity of a node measures its influence on another node and conversely, the sensitivity of a node measures how sensitive it is to random changes in one of its inputs.
- Phase transition and criticality:
-
Regarding the propagation of perturbations, one can distinguish between an ordered phase, where perturbations will not influence the network dynamics and an chaotic phase, where small perturbations will increase over time. Networks that operate at the transition of these two phases, such that perturbations are neither attenuated nor amplified on average, are called critical.
- Attractors:
-
In Boolean networks, dynamically stable patterns are called attractors. In their biological context, attractors may be interpreted as different cell types in models of cell differentiation or as cell states in models of cell signaling. Analyzing the influence of perturbations on attractor dynamics is thus of pivotal biological interest.
- Relevant and irrelevant nodes :
-
Only the perturbation of certain elements will move the system from one attractor to another. These dynamically relevant nodes are potential lever points for system intervention.
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Krawitz, P., Shmulevich, I. (2009). Boolean Modeling of Biological Networks. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_40
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