Computational Systems Biology

In this chapter, we introduced the basic concepts of cell attractors and showed that Waddington’s metaphoric epigenetic landscape has a formal basis in the attractor landscape. This conceptual framework helps to understand core properties of cell differentiation and ultimately, multicellularity. Specifically, we developed the concept of relative stability of network states on the epigenetic landscape, thus providing the elevation in the landscape picture a formal, quantifiable basis. We proposed methods to quantify the relative stability of attractor states in discrete gene networks models. We show in two examples that even with incomplete information about network structures, the use of Boolean networks can capture the essential outlines of cell fate dynamics and more importantly, permit the estimation of relative stability and the attractor transition barriers. These measures hold great promise for the rational design of the perturbation protocols for cell reprogramming in regenerative medicine. As the knowledge of the structure of GRNs for the development of various tissues will undoubtedly increase in the next decade, the utilization of such network information for therapeutic reprogramming may benefit from the concepts developed here.