Gene regulation and control network reconstruction method based on deep learning

The invention discloses a gene regulation and control network reconstruction method based on deep learning, and the method is used for reconstructing a network structure of a gene regulation and control network from observed messenger RNA (mRNA) concentration change time sequence data, namely a mutual regulation and control relation between genes. According to the method, a data-driven deep learning framework is provided to complete the reconstruction of a gene regulation and control network and simulation of gene regulation and control dynamics at the same time. The method consists of two modules which are trained together, namely an adjacent matrix generator for representing a connection structure of the gene regulation and control network and a dynamics predictor capable of predicting the concentration of each messenger RNA in the future. According to the method, the model can reconstruct the gene regulation and control network at higher precision, so that the regulation and controlrelation between genes c