
Mathematical Analysis of Some Reaction Networks Inducing Biological Growth/Decay Functions.
Author(s) -
Ksenia Ivova Tsocheva
Publication year - 2020
Publication title -
biomath communications
Language(s) - English
Resource type - Journals
eISSN - 2367-5241
pISSN - 2367-5233
DOI - 10.11145/bmc.2020.07.067
Subject(s) - gompertz function , realization (probability) , computation , computer science , process (computing) , logistic function , mathematics , perspective (graphical) , theoretical computer science , statistical physics , algorithm , physics , artificial intelligence , statistics , machine learning , operating system
In this work, we study some characteristics of sigmoidal growth/decay functions that are solutions of dynamical systems. In addition, the studied dynamical systems have a realization in terms of reaction networks that are closely related to the Gompertzian and logistic type growth models. Apart from the growing species, the studied reaction networks involve an additional species interpreted as an environmental resource. The reaction network formulation of the proposed models hints for the intrinsic mechanism of the modeled growth process and can be used for analyzing evolutionary measured data when testing various appropriate models, especially when studying growth processes in life sciences. The proposed reaction network realization of Gompertz growth model can be interpreted from the perspective of demographic and socio-economic sciences. The reaction network approach clearly explains the intimate links between the Gompertz model and the Verhulst logistic model. There are shown reversible reactions which complete the already known non-reversible ones. It is also demonstrated that the proposed approach can be applied in oscillating processes and social-science events. The paper is richly illustrated with numerical computations and computer simulations performed by algorithms using the computer algebra system Mathematica.