An Agent-Based Lattice Model for the Emergence of Anti-Microbial Resistance

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.

Publication DOI: https://doi.org/10.1016/j.jtbi.2019.110080
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences
Additional Information: © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Perceptron,Probabilistic model,Resistance reversal,Single-drug protocol,Statistics and Probability,Modelling and Simulation,Biochemistry, Genetics and Molecular Biology(all),Immunology and Microbiology(all),Agricultural and Biological Sciences(all),Applied Mathematics
Publication ISSN: 1095-8541
Last Modified: 01 Apr 2024 07:38
Date Deposited: 13 Nov 2019 10:34
Full Text Link:
Related URLs: https://linking ... 022519319304497 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2020-02-07
Published Online Date: 2019-11-12
Accepted Date: 2019-11-11
Authors: Alamino, R.C. (ORCID Profile 0000-0001-8224-2801)

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