Biological networks entropies: Examples in neural memory networks, genetic regulation networks and social epidemic networks

Jacques Demongeot, Mariem Jelassi, Hana Hazgui, Slimane Ben Miled, Narjes Bellamine Ben Saoud, Carla Taramasco

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Networks used in biological applications at different scales (molecule, cell and population) are of different types: neuronal, genetic, and social, but they share the same dynamical concepts, in their continuous differential versions (e.g., non-linearWilson-Cowan system) as well as in their discrete Boolean versions (e.g., non-linear Hopfield system); in both cases, the notion of interaction graph G(J) associated to its Jacobian matrix J, and also the concepts of frustrated nodes, positive or negative circuits of G(J), kinetic energy, entropy, attractors, structural stability, etc., are relevant and useful for studying the dynamics and the robustness of these systems. We will give some general results available for both continuous and discrete biological networks, and then study some specific applications of three new notions of entropy: (i) attractor entropy, (ii) isochronal entropy and (iii) entropy centrality; in three domains: a neural network involved in the memory evocation, a genetic network responsible of the iron control and a social network accounting for the obesity spread in high school environment.

Original languageEnglish
Article number36
JournalEntropy
Volume20
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes

Keywords

  • Attractor entropy
  • Biological networks
  • Dynamic entropy
  • Entropy centrality
  • Isochronal entropy
  • Robustness

ASJC Scopus subject areas

  • Information Systems
  • Mathematical Physics
  • Physics and Astronomy (miscellaneous)
  • Electrical and Electronic Engineering

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