May 24th, 2018
The networks used in biological applications at different scales (molecular, cellular and populational) are of different types, genetic, neuronal, and social, but they share the same dynamical concepts, the notion of interaction graph G(J) associated to their Jacobian matrix J, and also the concepts of frustrated nodes, positive or negative circuits of G(J), kinetic energy, entropy, attractors, structural stability, etc., are relevant and useful for studying the dynamics and the robustness of these systems.
We will give some general results available for both continuous and discrete biological networks and then, give some specific applications (a neural network involved in the memory evocation, a genetic network responsible of the Iron control and a social network accounting for the obesity spread in a high school environment).
