Characterisation of Singular Domains in Threshold-Dependent Biological Networks

Authors

  • Benitho Ngwu
    Department of Mathematics, Federal University Oye-Ekiti, Oye/Ekiti, Nigeria
  • Godwin C. E. Mbah
    Department of Mathematics, University of Nigeria, Nsukka/Enugu, Nigeria
  • Chika O. Mmaduakor
    Department of Mathematics, Federal University Oye-Ekiti, Oye/Ekiti, Nigeria
  • Sunday Isienyi
    Department of Mathematics & Statistics,Akanu Ibiam Federal Polytechnic Unwana, Afikpo/Ebonyi, Nigeria
  • Oghenekevwe R. Ajewole
    Department of Mathematics, Federal University Oye-Ekiti, Oye/Ekiti, Nigeria
  • Felix D. Ajibade
    Department of Mathematics, Federal University Oye-Ekiti, Oye/Ekiti, Nigeria

Keywords:

Discontinuous System, Singular Domain, Threshold-Dependent Network, Biological System, Piecewise Linear Models

Abstract

Threshold-dependent networks behave like piecewise smooth system which belongs to a class of systems with discontinuous right hand side. It can be studied with piecewise linear differential equations. At threshold values and their intersections, known as switching boundaries and surfaces, the state of such networks is not defined because of singularity at such points. These states are termed singular states or domains of the network. This study is to characterise, in terms of number, singular domains of any order in a network and the total number of such domains. It shall also propose new definitions for walls which are switching domains of order one. The new definition, which derives from Fillipov’s First Order Theory on characterisation of (sliding) wall, shall be shown to prove better than existing ones as it can reveal intrinsic behaviours in such networks.

Dimensions

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Published

2022-08-20

How to Cite

Characterisation of Singular Domains in Threshold-Dependent Biological Networks. (2022). Journal of the Nigerian Society of Physical Sciences, 4(3), 812. https://doi.org/10.46481/jnsps.2022.812

Issue

Volume 4, Issue 3, August 2022

Section

Original Research
Copyright & Licensing

Copyright (c) 2022 Benitho Ngwu, Godwin C. E. Mbah, Chika O. Mmaduakor, Sunday Isienyi, Oghenekevwe R. Ajewole, Felix D. Ajibade

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Characterisation of Singular Domains in Threshold-Dependent Biological Networks. (2022). Journal of the Nigerian Society of Physical Sciences, 4(3), 812. https://doi.org/10.46481/jnsps.2022.812

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