Combining genetic regulatory network models and a random matrix approach to solve large biological networks

In this thesis we study genetic regulatory networks using a minimal nonlinear<br/>model from literature and extend this to multi-compartment gene-to-gene interaction networks using both numerical simulations and random matrix theory.<br/>When we add perturbations to a system of two interaction networks, the largest<br/>eigenvalue becomes larger,...