Disease Gene Identification Based on Heterogeneous Network Impulse Dynamics

In the study of various diseases, such as cancer, it has always been a core direction to accurately find genes related to it. Existing research focuses more on the static structure of gene networks and pays insufficient attention to information in dynamic changes. In contrast, the method based on heterogeneous networks can more fully reflect the association pattern between genes and diseases by integrating the three types of network relationships of gene-gene, disease-gene, and disease-disease, and it is easier to locate the truly related genes. Among them, the heterogeneous network pulse dynamics model simulates the propagation process of the pulse signal in the network, and sorts the genes according to the strength of the nodes in the dynamic response, which is better than the traditional method. Based on this model, this paper reviews its research progress, focuses on its basic principles, applicable conditions, and existing limitations, compares the performance of several mainstream methods, and finally discusses the current problems and possible improvement directions.