Modeling of Tumor-Immune System Interaction with Stochastic Hybrid Systems with Memory: A Piecewise Linear Approach

Year 2021, Volume: 5 Issue: 1, 25 - 38, 31.03.2021

Nurgul Gokgoz Hakan Öktem

https://doi.org/10.31197/atnaa.773390

Cited By: 3

Abstract

In this work, we benefit from hybrid systems that are advantageous because of their
analytical and computational usefulness in the case of inferential modeling. In fact,
many biological and physiological systems exhibit historical responses such that the
system and its responses depend on the whole history rather than a combination
of historical events. In this work, we use and improve hybrid systems with memory
(HSM) in the subclass of piecewise linear differential equations. We also include
stochastic calculus to our model to exhibit uncertainties and random perturbations
clearly, and we call this model stochastic hybrid systems with memory (SHSM).
Finally, we choose tumor-immune system data from the literature and show that
the model is capable to model history dependent behavior.

Keywords

hybrid systems, functional differential equations, pattern memorization, multistationarity, regulatory dynamical systems

Project Number

104T133

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