Information Thermodynamics for Time Series of Signal-Response Models.

Auconi, Andrea; Giansanti, Andrea; Klipp, Edda

The entropy production in stochastic dynamical systems is linked to the structure of their causal representation in terms of Bayesian networks. Such a connection was formalized for bipartite (or multipartite) systems with an integral fluctuation theorem in [Phys. Rev. Lett. 111, 180603 (2013)]. Here we introduce the information thermodynamics for time series, that are non-bipartite in general, and we show that the link between irreversibility and information can only result from an incomplete causal representation. In particular, we consider a backward transfer entropy lower bound to the conditional time series irreversibility that is induced by the absence of feedback in signal-response models. We study such a relation in a linear signal-response model providing analytical solutions, and in a nonlinear biological model of receptor-ligand systems where the time series irreversibility measures the signaling efficiency.

THERMODYNAMICS; TIME series analysis; BIPARTITE graphs; BIOLOGICAL models; PROBABILITY density function

Entropy, 2019, Vol 21, Issue 2, p177

1099-4300

Academic Journal

10.3390/e21020177