Resolution:
## Figure 2.
Subsystems in the example Boolean network model. (A, B) Network and Boolean functions for a simple Boolean network model. If the
logical condition in a Boolean function is satisfied (for node n_{i}), then that node takes state 1 at the following time step (s_{i}(t + 1) = 1). Otherwise, if the logical condition fails, s_{i}(t + 1) = 0. Interactions in the model are summarised by the network edges in A (red
arrow = activation, blue dot = inhibition). (C) A_{1}, ..., A_{4 }are the 4 possible attractors for the Boolean network model in A, B, which are consistent
with both synchronous and asynchronous updating schemes. Each column corresponds to
a node in the model, whilst each row corresponds to an attractor state. White/Black
corresponds to the node having state 1/0 in the attractor state. Once the system enters
an attractor it continually cycles through those attractor states (e.g. z_{0}, z_{1}, z_{2}, z_{3}, z_{0}, z_{1}, z_{2}, z_{3}, z_{0}, z_{1 }after the system enters A_{1}). (D) 6 Subsystems identified for this model, corresponding to sub-dynamics that
are conserved across/distinguish sets of attractors from C. These were identified
by applying the new method from this paper to the 4 attractors A_{1}, ..., A_{4}. Each column corresponds to a node in the model, whilst each row corresponds to a
partial state. White/Black corresponds to the node having state 1/0 in the partial
state.
Irons and Monk |