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Find a cure for disease
through networks
Boolean networks have been widely used to model gene regulatory networks and signaling pathways because ordinary differential equation (ODE) formalisms are constrained by the size of the sub-network and the dearth of kinetic and parametric information. Using Boolean networks, it is possible to describe the condition of the gene, whether activated or repressed, using the binary state ({0, 1} = {on, off}). It may also be visualized as a graph, G {v,e} with vertices v (genes) and edges e (interactions). The Boolean analysis panel accepts two inputs, vertices and edges, for converting the network into matrices required for computation. An option is also available for specifying non-regulated nodes (self-degrading nodes). An example has been provided (default) in the window below following which users may create their own Boolean network.

Boolean Network
Synchronous Update (Current release:BN1.0)
* Download Network Examples : Here
Number of Nodes

Number of Edges

Self-degrading nodes

Boolean Rules

Boolean functions

Entire state space
Singleton attractors by modular method:Use Boolean Rule-2