Resolution:
## Figure 2.
The principle of automatic network reconstruction explained with the help of a trivial
example. a) The input for the reconstruction algorithm is a time series data set that describes
the time-course of the components of interest (A,B,C) with discrete values as a causal
sequence of events. At time t_{2 }the system reached its terminal state, i.e. the values of all components have reached
their final level. In the simplest form, the entries are boolean (0,1). b) Shows the
reaction vector of the transition in e). A reaction vector corresponds to the incidence
matrix of an individual transition or to a column in the incidence matrix of a Petri
net. c,d) The presence of the components at given time points is represented by tokens
in places assigned to the components. The algorithm evaluates those places the marking
of which has changed between two successive time points and e) connects these places
with transitions that cause the observed flow of tokens in the reconstructed Petri
net.
Durzinsky |