Nonlinear and measure-theoretic methods for large biological networks

Date: Thu. February 11, 2021
Organized by: FAU DCN-AvH, Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany)
Title: Nonlinear and measure-theoretic methods for large biological networks

Speaker: Prof. Dr. Benedetto Piccoli
Affiliation: Rutgers University, USA

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.


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