Patent ID: 11960802
Assignee: TURBINE SIMULATED CELL TECHNOLOGIES LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 25:
26. A non-transitory computer program product for identifying biological components in a real complex system of biochemical nature, wherein the biological components are targets for therapeutic intervention by therapeutic agents, the product comprising computer readable instructions which, when run on a computer, cause the computer to:
a) model the system with a network of objects represented by networks points and relations between the objects represented by edges between the network points, wherein the states of the objects are described by a parameter set and the relations associated with the edges are described by functions of time, wherein the objects are biological components;
b) for each object of the system, obtain values for each parameter of the parameter set for an initial state and a desired target state thereof, wherein the initial state corresponds to a diseased state;
c) set the initial values and the desired target values of the parameters of the network points;
d) automatically generate an initial set of test excitations for at least one point of the network using a predetermined metaheuristic algorithm, the initial set of test excitations including a predetermined number of test excitations defined by the metaheuristic algorithm;
e) simulating the behavior of the network using the set of test excitations;
f) detect whether a simulation termination condition in a given stimulation step is true and if so, stop the simulation;
g) after the simulation is stopped, calculate and store, for each network point, the difference between the parameter values belonging to the desired target state and the parameter values produced by the simulation;
h) based on the differences and number of test excitations, automatically generate a next set of test excitations using the predetermined metaheuristic algorithm, the next set of test excitations being generated to more closely approach the target state based on the previous test excitations having the smallest difference between the parameter values belonging to the desired target state and the parameter values produced by the simulation, and the number of text excitations in the next set being defined by the metaheuristic algorithm;
i) iteratively repeat steps e)-h) to reduce the difference between the parameter values produced by the simulations and the parameter values of the target state until a predetermined termination condition is satisfied;
j) from among the stored simulation results, select the simulation result best matching the desired target state, where the test set of excitations which produced the best matching simulation results is regarded as a final excitation set transferring the network from its initial state to its target state; and
k) outputting the final excitation set as designed targets for therapeutic intervention by therapeutic agents in the system.