Network Dynamics as an Inverse Problem --Detecting network size and topology from time series

Datum

19.10.2023

Zeit

11:00 - 12:00

Sprecher

Marc Timme

Zugehörigkeit

Institute for Theoretical Physicsand Center for Advancing Electronics Dresden (cfaed), TU Dresden

Serie

MPI-CBG Thursday Seminar

Sprache

en

Hauptthema

Biologie

Host

Carl Modes

Beschreibung

The dynamics of biological networks enables the function of a variety of systems, including metabolic, gene-regulatory and neural circuits. To date, it remains unclear how to extract key features of networks if only time series data from (some) units are available. Here we report on recent progress on detecting structural features from observed dynamics. First, we demonstrate how to identify the number N of dynamical variables making up a network -- arguably its most fundamental property -- from recorded time series of only a small subset of n<N variables. Second, we sketch approaches to uncover network topological features from observed nodal time series data. We demonstrate first steps of applying the general theoretical methods developed to simulated models of biological and artifical systems. This is work with Jose Casadiego, Mor Nitzan, Hauke Haehne, Georg Boerner and others. [1] Topical Review: Marc Timme & Jose Casadiego, J. Phys. A 47:343001 (2014). [2] Casadiego et al., Nature Comm. 8:2192 (2017). [3] Nitzan et al., Science Adv. 3:e1600396 (2017). [4] Haehne et al., Phys. Rev. Lett. 122:158301 (2019).

Letztmalig verändert: 20.10.2023, 07:40:35