Structural Modeling and Intervention of Gene Regulatory Networks for Ultra-Early Disease Prevention

Prediction and prevention of complex diseases are essential to secure human health and social benefits. It is known that gene regulatory networks (GRNs) have critical roles in many biological activities and also in the process of disease progression. Identifying the structure of GRNs leads to accurate prediction and proper intervention for preventing complex diseases. In this paper, we develop a structural modeling method for GRNs. First, the dynamics of each gene’s expression are described as a discrete-time linear state equation. Then, we develop model-based and data-based robust intervention methods for GRNs such that the system matrix in the state equation is manipulated, aiming at improved stability. Finally, the presented structural modeling and intervention methods are demonstrated in a numerical experiment.