Nonlinear and measure-theoretic methods for large biological networks (B. Piccoli, Rutgers University, USA)
Nonlinear and measure-theoretic methods for large biological networks
Speaker: Prof. Dr. Benedetto Piccoli
Affiliation: Rutgers University, USA
Zoom access data: Please contact marius.yamakou@fau.de
Abstract: In this talk, we will present two new techniques developed to study complex biological networks.
First, we will analyze new methods for the simulation of a large biochemical network with focus on QSP
(Quantitative Systems Pharmacology), virtual patient populations, and tuberculosis. The main idea is to combine
knowledge from the fields of: Markov Chains, Compartmental Systems, Control Theory, and others to provide a generalize
class of graphs and results on the associated dynamics. Secondly, we will describe a general framework to study reaction-diffusion
equations on time-evolving manifold and, more generally, mean-field limits. This approach is useful to study problems in
Developmental Biology when various ligands diffuse on growing embryos (or egg chambers) to activate morphogenic pathways.