Berlin 2024 – scientific programme
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DY: Fachverband Dynamik und Statistische Physik
DY 57: Networks: From Topology to Dynamics II (joint session DY/SOE)
DY 57.6: Talk
Friday, March 22, 2024, 11:15–11:30, BH-N 128
Exploiting memory effects to detect the boundaries of biochemical subnetworks — •Moshir Harsh1, Leonhard Vulpius1, and Peter Sollich1,2 — 1Institut für Theoretische Physik, Georg-August-Universität Göttingen, Göttingen — 2Department of Mathematics, King’s College London, London WC2R 2LS, UK
Partial measurements of biochemical reaction networks are ubiquitous and limit our ability to reconstruct the topology of the reaction network and the strength of the interactions amongst both the observed and the unobserved molecular species. Here, we show how we can utilise noisy time series of such partially observed networks to determine which species of the observed part form its boundary, i.e. have significant interactions with the unobserved part. This opens a route to reliable network reconstruction. The method exploits the memory terms arising from projecting the dynamics of the entire network onto the observed subnetwork. We apply it to the dynamics of the Epidermal Growth Factor Receptor (EGFR) network and show that it works even for substantial noise levels.
Keywords: Network inference; Memory; Dynamics of networks; Bayesian regression; Biochemical networks