A novel critical time analysis approach for genetic regulatory networks

The expression levels of certain molecular markers can show signs of the beginning of a disease. Effective treatment of the disease demands the identification of the time point when the probability of the corresponding genetic state reaches a critical value. This paper presents a new methodology which utilizes eigenvalue decomposition of the reaction matrix of the system that enables us to use efficient bisection method for finding the aforementioned critical time point. The results show significant improvement of computational efficiency over existing fine scale models based on Stochastic Master Equations.