Abstract
This work introduces a new probabilistic agent-based lattice model for studying the emergence of anti-microbial resistance (AMR) and proposes a new proxy to measure it: the average death probability of the population under the action of the AMD. Both analytical studies and computer simulations of the microscopic behaviour of a bacterial culture interacting with anti-microbial drugs on a discrete lattice are carried out by focusing on the dynamics of this quantity. A unique genotype-phenotype map and classes of AMDs follow as emergent properties and their effects on the possible reversal of resistance are analysed. We also discuss briefly the possibility of using machine learning techniques to learn the model parameters.
Original language | English |
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Article number | 110080 |
Journal | Journal of Theoretical Biology |
Volume | 486 |
Early online date | 12 Nov 2019 |
DOIs | |
Publication status | Published - 7 Feb 2020 |
Bibliographical note
© 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/Keywords
- Perceptron
- Probabilistic model
- Resistance reversal
- Single-drug protocol