Patent ID: 7401056

Claim:
Apparatus for analyzing a biological system defined by-multivariable data sets including a plurality of perturbations (inputs) and measured response (outputs) variables, said apparatus comprising: a neural network capable of receiving signals contained in said data sets and processing said inputs according to an artificial intelligence program to yield the outputs; and means for obtaining a trained matrix of weight parameters for said neural network and said data sets through a sequence of iterations, starting at random guess for the weight parameters, and correcting the trained weight matrix according to a learning rule until the errors between the processed inputs and the outputs diminishes; means for obtaining an average matrix of weight parameters of a multitude of trained weight matrices including sequentially and repeatedly averaging the multitude of trained weight matrices, each initialized by a different set of a plurality of random weight parameters, until the averaged matrix of weight parameters converges to not greater than 10% variance; means for evaluating the relationship between said variables from said averaged matrix of weight parameters converged to not greater than 10% variance; and means for collecting data sets which include a plurality of induced and measured variables which characterize stimuli applied to cells and responses of said cells to said stimuli, wherein said averaged matrix of weight parameters converged to not greater than 10% variance provide identification of finger prints of complex cellular states, wherein said data sets comprise experimentally determined data which characterize variations in measurable components of a biological process.