Inference of genetic networks using neural network models

We propose a new method for the inference of the genetic networks. The proposed method uses a neural network model to describe the genetic network. The inference of the neural network model of the genetic network is defined as the function optimization problem. As the function optimizer for this problem, a genetic local search is used. At this time, to enhance the probability of finding a reasonable solution, we introduce a priori knowledge about the genetic network into the objective function. In this paper, we also propose the method based on the sensitivity analysis to interpret the optimized neural network model. Through artificial genetic network inference problems, we verify the effectiveness of the proposed method.