Guillermo Gallardo – Athena
Principal Process Analysis of biological models
Stefano Casagranda – Biocore
Understanding the dynamical behavior of biological systems is challenged by their large number of components and interactions. We design a method for dealing with this complexity, called Principal Process Analysis (PPA). The knowledge of the system trajectories allows us to decompose the system dynamics into processes that are active or inactive with respect to a certain threshold value. We eliminate from the model processes that are always inactive, and inactive in one or several time windows. This reduces the complex dynamics of the original model to the much simpler dynamics of the core processes, in a succession of sub-models that are easier to analyze. In conclusion, PPA is an useful tool for analyzing the complex dynamical behavior of biological systems.
Neutralising antibodies prevent PRRS viremia rebound: evidence from a data-supported model of immune response
Natacha GO – BIOCORE
Understanding the mechanisms determining the within-host variability in infection is a key issue to better understand and control infection spread. The Porcine Respiratory and Reproductive Syndrome virus (PRRSv) is a major challenge for the swine industry worldwide, host infections exhibit a high variability and immune mechanisms determining its dynamics are still poorly understood. We identified immune mechanisms that could explain observed variability in infection profile (rebounders vs no-rebounders) using a mathematical model of the within-host dynamics fitted to experimental data. Our results provide new insides and can guide vaccine design and genetic selection to prevent rebounders.