Evolutionary Inference of a Biological Network as Differential Equations by Genetic Programming

Inferring a biological network from a set of observed time series is becoming more important as technologies such as DNA microarrays have been developed rapidly in recent years. Many models have been proposed to describe the biological network. Among them is a system of differential equations, which is flexible to represent the complex relationships among their components. In most of the previous studies [1], the form of the equations was fixed because it was difficult to determine the suitable form giving the similar time series to the target. We have used the arbitrary form in the right hand side of the equation (1) as the model of the network [2], in which Genetic Programming (GP) has been successfully applied to inferring the biological network.